IoT-Based Mushroom Cultivation System with Solar Renewable Energy Integration: Assessing the Sustainable Impact of the Yield and Quality

Abstract

The conventional method of mushroom cultivation can be labor-intensive and produce limited yields. Due to the humidity and temperature in the summer season, mushroom production is significantly diminished. The growth of each mushroom species depends on the consistency of care, the skill of experienced farmers, and crucial cultivation parameters such as temperature, humidity, irrigation, and exposure to sunlight. This study aims to implement an IoT-enabled cultivation system to control and monitor the environmental parameters of Indian mushroom cultivation within the proposed innovative framework, as compared to conventional methods. The IoT-based cultivation system consists of hardware components, circuit connections, software, and algorithms. This study confirms that consistent control of environmental parameters, such as temperature and relative humidity, by a dynamic climate promotes mushroom growth that is superior to conventional cultivation. Our findings reveal a substantial increase in the yield and quality of mushrooms, demonstrating the tangible advantages of applying an innovative approach. Traditional cultivation yielded an average of 4.118 kg, whereas IoT-based cultivation systems produced an average of 5.306 kg. The t-test statistic comparing yields has highlighted the significance of the observed differences with a p-value of 0.0000. The research contributions are to design and demonstrate the IoT-enabled system innovation with solar renewable energy, illustrating the effect of mushroom production and quality on the economic market analysis of mushroom cultivation in the direction of environmentally sustainable and green agricultural practices. This study’s comprehensive perspective can provide farmers, agricultural professionals, and policymakers with valuable insights regarding the future of mushroom cultivation, particularly the reduction of carbon emissions and energy consumption.

1. Introduction

Mushrooms are nutritionally dense and have diverse human applications. Mushroom cultivation has been an essential aspect of agriculture for centuries, as mushroom production has demonstrated enormous potential in terms of products with added value, market demand, consumer perception, and health benefits [1,2,3]. Numerous studies have investigated the nutritional qualities of mushrooms as well as their commercialization and value enhancement [4,5,6]. Sara et al. [7] have emphasized the significance of mushroom-derived eco-friendly industrial products. Lu et al. [5] have investigated mushroom cultivation, bioactivity, and application. Their study has discovered that mushrooms contain prebiotics, affecting the gut microbiome and human health. The study indicates that mushroom cultivation offers promising economic and nutritional benefits, urging further investigation of its untapped potential. As the global demand for mushrooms continues to rise, there is an ever-increasing need to investigate innovative approaches that can boost mushroom farming’s productivity, sustainability, and efficiency [8].

Mycelium growth dynamics, environmental factors, substrate optimization, and quality control are just a few of the techniques in the landscape of fungal cultivation. Rämä and Quandt [9] have investigated cultivability techniques for enhancing filamentous fungi, ranging from culture media formulations and chemical growth factors to in situ culturing and synthetic biology methods. Lee et al. [10] have developed a precise method for quantifying mycelial growth by analyzing the intensity of microscopic images. In addition, Landingin et al. [11] have investigated the effects of culture media, pH levels, and physical factors on Agrocybe cylindracea’s growth dynamics and fruiting body production. By modifying the growth substrate conditions, Antinori et al. [12] have elucidated the manipulation of the morphological, chemical, and hydrodynamic properties of Ganoderma lucidum mycelium. This research provides the adaptable factors and techniques necessary for optimizing fungal cultivation for actual applications ranging from the discovery of natural products to food fermentation and material production.

Innovation in the field of fungi cultivation is of the utmost importance. Studies [9,13,14,15] have demonstrated industrial fungal farming from technological standpoints. A substantial global increase in the production and cultivation of novel edible fungi species has been accompanied by the use of advanced technologies. Moreover, the significance of enhancing cultivability for natural product discovery is highlighted in [9], which highlights the need for techniques enhancing the cultivability of filamentous fungi, including optimized culture media formulations, chemical growth factors, and in situ culturing. Using edible fungi as an example, Luo [14] explores the formation, characteristics, and functional aspects of edible fungi-based micro landscapes using innovative design methodologies. In addition, Huang et al. [15] have investigated the development of a curriculum designed to foster applied expertise in edible fungi cultivation. This study’s interdisciplinary synthesis of innovative technologies, improved cultivability, design methodologies, and education exemplifies the cutting-edge fungi cultivation innovations.

While innovative fungi cultivation plays an important role in industrial fungi farming, research problems raised by traditional mushroom cultivation rely heavily on local farmers’ manual cultivation and management techniques. Monitoring and controlling crucial cultivation parameters such as temperature, humidity, irrigation, and exposure to sunlight can be challenging with conventional methods [16]. Suboptimal conditions may lead to decreased yields, decreased quality, and increased susceptibility to diseases and pests. Compared to mushroom growth, particularly in tropical environments, the problems associated with warmth and condensation in mushroom cultivation are relatively less significant [17]. From the initial 60 packs of mushrooms harvested during the summer, only four–five packs were harvested, a reduction of 8.33% on average. Moreover, the heat occasionally caused immature buds to wither [18]. Integrating Internet of Things (IoT) technologies is a viable solution that research lacks for overcoming these limitations. Monitoring and regulating environmental conditions in mushroom cultivation is feasible with the advent of IoT systems. By leveraging IoT sensors, actuators, and data analytics, farmers can achieve real-time monitoring and control over cultivation parameters, thereby ensuring a mushroom-friendly environment. Numerous researchers have utilized IoT in mushroom cultivation for various purposes and designs. Hendinata and Fikri [19] have developed an IoT-based monitoring system for temperature and humidity in mushroom cultivation rooms. Chong et al. [20] have designed an IoT-based environmental control and monitoring system tailored for home-based mushroom cultivation. Aggarwal and Singh [21] have further investigated the application of IoT technologies in mushroom cultivation, highlighting the associated benefits and drawbacks. Implementing an IoT-based monitoring and control system in a mushroom farm by Kassim et al. [22] resulted in increased yields and optimized resource utilization. The IoT-based system enables the improvement of real-time environmental data and remote monitoring and control in real-world applications by applying the roles of existing IoT-based studies to mushroom cultivation.

In addition, the IoT has been a driving force behind the remarkable potential for technological innovations to revolutionize agriculture. Concurrently, combining renewable energy sources into agricultural systems has gained momentum, resulting in positive environmental effects. Applying IoT-based renewable energy sources emerges as a transformative strategy [23] within the specifications for Indian oyster mushroom cultivation. Thus, this study examines the potential for substantial effects on agricultural productivity and the preservation of the environment. By harnessing renewable energy, such as solar panels, to power various aspects of growing mushrooms, it is possible to significantly reduce the carbon emissions historically associated with conventional energy sources [24]. The innovative system innovation aligns perfectly with India’s commitment to reducing carbon emissions and promoting sustainable agricultural practices. By replacing energy derived from fossil fuels with cleaner, renewable alternatives, the cultivation process becomes more environmentally friendly and economically viable in the long run [25,26]. Agrivoltaics research considers the joint use of land to produce agricultural products and energy, an investigation rapidly gaining popularity and necessitating an analysis of the technical and economic viability of using solar energy in conjunction with agriculture [27]. This study’s motivation also focuses on an integration representing a strategic symbiosis between technological innovation and agricultural progress, highlighting how the transition to renewable energy not only reduces carbon emissions but also paves the way for resilient and sustainable agricultural practices in the context of the preservation of the environment. Incorporating renewable energy sources into cultivating Indian oyster mushrooms is an example of sustainable system innovation.

This study aims to design, develop, and investigate the impact of an IoT-enabled adaptively controlling environmental cultivation system with solar renewable energy versus a conventional method for Indian oyster mushroom cultivation regarding yield and quality. The synergy of IoT technologies empowers cultivators to design complex ecosystems that redefine precision agriculture.

The contributions of the proposed study are economics, agricultural technology, and environmental sustainability. The environmental control system for mushroom cultivation integrates Internet of Things (IoT) technologies and solar renewable energy sources, offering significant economic potential. Real-time monitoring and control enhance yield and quality, thereby increasing the economic viability of mushroom farmers, who can now compete effectively on the market and generate greater revenue streams. In addition, the research proves technological advancements in agriculture by implementing an advanced IoT-enabled cultivation system. This exemplifies the transformative potential of precision agriculture, which refines and stabilizes environmental conditions while introducing sophisticated resource management techniques. Automation and data analytics play a crucial role in improving mushroom cultivation for technical sophistication and efficiency. In addition, the study is committed to environmental sustainability by utilizing solar renewable energy sources, specifically solar energy. This is consistent with global efforts to reduce carbon emissions and promote sustainable agricultural practices, thereby reducing the ecological impact of mushroom farming in relation to climate change concerns, particularly in tropical environments. Resource efficiency is also pivotal, emphasizing optimal resource management and waste reduction, benefiting both environmental conservation and cost savings for farmers. This strategy highlights the economic rationale for adopting innovative practices, thus improving the overall profitability of mushroom cultivation. The study concludes by examining the capacity for growth and adaptation of IoT-integrated and solar renewable energy-driven mushroom cultivation methods at various production metrics. Scalability ensures the inclusion of both small- and large-scale farmers, whereas adaptability tailors the system to a variety of environmental conditions. In conclusion, this research represents a groundbreaking investigation into mushroom cultivation practices, with the potential to yield substantial economic, technological, and environmental benefits.

Moreover, in an era characterized by growing concerns about climate change and environmental sustainability, incorporating solar renewable energy sources presents an opportunity to reduce mushroom farming’s ecological footprint. Utilizing solar panels, for instance, can provide a dependable and sustainable energy source for mushroom cultivation IoT systems. By adopting solar renewable energy, mitigating greenhouse gas emissions, and contributing to a greener and more sustainable agricultural sector, farmers can reduce their reliance on nonrenewable resources. The authors will address the following research questions:

(1)

How does the integration of IoT technologies and solar renewable energy sources affect the yield and quality of mushrooms compared to conventional cultivation methods?

(2)

What are the technical challenges and implementation factors associated with integrating IoT systems and solar renewable energy sources into mushroom farming practices?

(3)

To what extent are IoT-integrated and solar renewable energy-driven cultivation methods scalable and adaptable in the context of mushroom production?

2. Materials and Methods

This section describes the research materials and methodology used to outline the framework and processes for designing and developing IoT-based cultivation with solar renewable energy, as shown in Figure 1. This research focuses on utilizing IoT-based technologies and solar renewable energy sources to move from conventional to innovative fungal cultivation techniques effectively. The investigation of potential design techniques, analysis of the comprehensive capabilities of traditional and IoT-enhanced cultivation systems alongside related considerations, development of an innovative system framework based on separation of concerns, validation of the methodology through a practical application utilizing the innovative cultivation framework, and a summary of the research methodology results are presented. The proposed framework incorporates a separation of concerns and practical methodologies aligned with IoT-enhanced and solar renewable energy-supported systems. A practical use case of Indian oyster mushroom cultivation demonstrates the success of implementing the innovative cultivation system framework designed, producing a supported result for an effective cultivation framework approach. This paper presents an innovative mushroom cultivation framework to address the research challenges associated with advancing the understanding of the efficacy of IoT technology in fungal cultivation, encompassing an IoT-based system’s hardware, software, and data interactions.

As depicted in the research framework for designing and developing IoT-based cultivation with renewable energy in Figure 1, this study consists of several crucial phases. Transitioning from conventional cultivation techniques to innovative IoT-based techniques while integrating renewable energy sources into the cultivation processes constitutes these stages. The methodology for the transformation processes of the cultivation framework includes an analysis of the current traditional cultivation practices, including growth dynamics, environmental conditions, resource management, and system functionality. This evaluation includes substrate types, growth parameters, temperature control, and energy usage. Significant differences between conventional and IoT-based cultivation systems, including cultivation models, growth dynamics, resource utilization, automation capabilities, energy efficiency, and cost considerations, have been identified and incorporated into the analysis to address strategic concerns. All factors influencing traditional and IoT-based cultivation practices, such as growth patterns, resource management, environmental control, and automation capabilities were carefully considered. The proposed cultivation framework was developed iteratively, with constant engagement and input from previous research and local cultivators, to ensure its precise alignment with the cultivation project’s unique requirements and objectives. Nonetheless, it is essential to emphasize that the specific requirement of the study was a complete transformation of the cultivation system innovation. By mapping and designing the framework architecture between traditional and IoT-based cultivation systems, techniques such as separation of concerns, IoT sensors, data analytics, automated control mechanisms for growth conditions, energy sources, and resource optimization were utilized to facilitate the design of the innovative system with renewal energy. In addition, the preparatory phase included framework design, cultivating factors, and system information processes to ensure the compatibility and integrity of the newly integrated system.

The final step in validating the practical innovation of the cultivation system was to validate the successful outcomes of cultivation practices transitioning from the traditional system to the IoT-based framework, including growth monitoring, data analysis, energy integration, and system validation. This step entailed real-time monitoring of growth conditions, data analysis for growth trends, incorporating renewable energy sources, and reconciliation of resource utilization. The objective of this procedure was to ensure that the transition to an IoT-based cultivation system, bolstered by incorporating renewable energy, effectively enhances growth dynamics, optimizes resource utilization, and substantially reduces environmental impact.

2.1. Traditional Concerns of Fungi Cultivation Factors

Essential factors for the agriculture of Indian oyster mushrooms include the substrate used for cultivation, the supporting facilities, and the timing of harvesting. Wongamthing et al. [28] discovered that oyster mushroom yield was significantly affected by substrate type, with rice straw and wheat straw producing the highest yield. Kusrini, Sulistiawati, and Imelda [29] identified market demand, capital, and labor availability as the most important criteria for sustainable oyster mushroom agribusiness. Hemalatha 2018 discovered that the timing of spawning affected the yield of Pleurotus pulmonarius, with spawning in December and January being optimal for achieving superior yields. Randive [30] previously discovered that cultivating oyster mushrooms on agricultural waste, such as paddy straw and wheat straw, produced a high yield and nutritional value.

Utilizing manual intervention and time-tested techniques passed down through the generations, mushroom cultivation has been practiced traditionally for centuries. Despite being time-tested, traditional cultivation methods frequently rely on farmers’ cultivation skills and knowledge, as well as the assessment of specific environmental conditions and prudent management practices in general.

• Preparing the substrate entails: Preparing the substrate, which serves as the mushroom’s growing medium, is the first step in traditional mushroom cultivation. Typical substrates include agricultural wastes such as straw, sawdust, wood chips, or a combination of these materials. The substrate is typically sterilized or pasteurized to eliminate competing microorganisms and create favorable conditions for mushroom growth. Indian oyster mushrooms can be cultivated on various substrates. Cotton seed and paper waste were discovered to be the most suitable substrates for oyster mushroom cultivation, whereas sawdust was the least suitable. Yang et al. [31] discovered that tea waste could be an efficient and cost-effective medium for oyster mushroom cultivation. The yield and biological efficiency of oyster mushrooms are affected by substrate formulation, supplementation, and composting conditions, according to Vieira and Andrade [32]. Tesfaw et al. [33] evaluated locally accessible substrates for oyster mushroom cultivation and discovered that wastepaper and gabi wastes alone or combined with sawdust produced more oyster mushrooms than other substrates. Overall, the papers suggest that the selection of substrate for Indian oyster mushroom cultivation should be based on factors such as cost, yield performance, and availability.
• Spawning: The substrate is prepared and inoculated with mushroom spawn, which contains mycelium, the vegetative portion of the fungus; then, the spawning process can begin. The spawn is the starting point for mushroom development. Traditionally, spawn is obtained from previous mushroom harvests or purchased from specialized vendors. Utilizing suitable substrates and spawn preparation techniques are the best practices for maintaining spawning in Indian oyster mushroom cultivation. Wongamthing et al. [28] discovered that rice straw and wheat straw produced the highest yield of oyster mushrooms, while Chitra et al. [34] determined that MDU-1 is the best oyster mushroom variety for the climate of Tiruchirapalli. Liao et al. [35] provided a comprehensive protocol for cultivating oyster mushrooms, from mother culture isolation to spawn preparation, that amateur and professional cultivators can use. Pokhrel [36] suggested that locally and easily accessible substrates such as corn cob, vegetable residue, and wastepaper can be used as supplements for oyster mushroom cultivation alongside rice bran and chicken manure.
• Construction of a fruiting chamber: A fruiting chamber or growing house is constructed to provide optimal conditions for mushroom fruiting. The room may contain beds, stacked shelves, or wooden racks. The objective is to create a controlled environment replicating the natural conditions necessary for mushroom growth. Considering the best practices for maintaining the growing house for cultivating Indian oyster mushrooms from mother culture isolation to spawn preparation, Liao et al. [35] provide a detailed protocol for cultivating oyster mushrooms. Pokhrel [36] discovered that corn cob substrate supplemented with rice bran produced the highest yield and biological efficiency for oyster mushroom cultivation. Tesfaw et al. [33] analyzed locally accessible substrates and materials for oyster mushroom cultivation and discovered that wastepaper and gabi wastes alone or combined with sawdust produced more oyster mushrooms than other substrates. Thakur [37] examined the current status and future prospects of tropical mushroom cultivation in India. He discovered that women in self-help groups primarily engage in oyster mushroom cultivation, providing a significant source of income.
• Control of humidity and temperature: Maintaining humidity and temperature levels is essential for mushroom cultivation. Traditionally, this is accomplished manually through periodic misting or water spraying to maintain high humidity. Adjusting the ambient temperature, installing insulation, or utilizing natural ventilation are all methods for regulating temperature. Using technology to control and monitor temperature and humidity effectively maintains optimal conditions [38] for cultivating Indian oyster mushrooms. Sulistyanto et al. [39] and Hishamuddin [40] utilized Arduino UNO and the IoT framework to develop temperature and humidity control system prototypes. Chong et al. [20] also created a prototype utilizing the IoT platform Cayenne, whereas Sulistyanto et al. [39] utilized a fuzzy logic controller to control temperature and humidity. These previous studies demonstrated that their respective systems effectively maintained the optimal temperature and humidity for oyster mushroom cultivation.
• Light management: Mushrooms are typically grown in low-light environments because they thrive in darkness or with limited exposure to light. The fruiting chamber is designed to minimize direct sunlight while providing diffused or artificial light as required. Traditional techniques frequently rely on dim or filtered light to facilitate mushroom growth. Utilizing technology and preparing the substrate correctly can optimize the light management for Indian oyster mushroom cultivation. Shakir et al. [38], Sulistyanto et al. [39], and Mohammed et al. [41] discussed using IoT technology to monitor and control the environment for oyster mushroom cultivation automatically, which can increase productivity and decrease labor expenses. Vieira and Andrade [32] and Girmay et al. [42] deliberated the significance of substrate preparation for oyster mushroom cultivation, with Vieira and Andrade [32] discovering that substrate composted for seven days with conditioning exhibited higher yield and biological efficiency, and Girmay et al. [42] discovering that cotton seed and paper waste were suitable substrates for oyster mushroom cultivation. Overall, the papers suggest that the best practices for maintaining light management for the cultivation of Indian oyster mushrooms involve the application of technology and the proper preparation of the substrate.
• Air circulation and ventilation: Sufficient air circulation within the fruiting chamber is essential for sustaining a healthy growing environment and preventing carbon dioxide buildup. To ensure adequate air circulation, traditional methods may involve manual fanning or installing passive ventilation systems. Maintaining adequate air circulation and ventilation is essential for cultivating Indian oyster mushrooms. Yum and Kim [43] found that reversible air-circulation fans increased air uniformity compared to unidirectional fans. Using microcontrollers and IoT frameworks, Chong et al. [20] and Sihombing et al. [44] developed temperature and humidity control systems to maintain optimal conditions for mushroom growth. Shakir et al. [38] and Sunghyoun et al. [45] installed air circulation fans in a multilayered shelf system to increase air uniformity and maintain stable temperature and humidity levels. Overall, these studies indicated that using technology to control air circulation and ventilation can improve the quality and yield of Indian oyster mushroom cultivation.
• pH management: For optimal mycelial growth and fruiting, it is essential to maintain the correct pH level in the substrate. Generally, Indian oyster mushrooms are slightly acidic to neutral in pH. Elattar et al. [46], Hemalatha et al. [47], Vieira and Andrade [32], and Tesfaw et al. [33] all focus on different aspects of oyster mushroom cultivation, such as substrate preparation, growth pattern, and yield, when discussing the optimal pH range for Indian oyster mushroom cultivation. Nevertheless, a few of the papers emphasize the significance of pH in mushroom cultivation. For instance, Vieira and Andrade [32] found that substrate formulation and composting conditions affected oyster mushrooms’ yield and biological efficiency. The effects of pore size, temperature, and relative humidity on mushroom growth were evaluated by Tesfaw et al. [33]. Although none of the papers directly answer the research question, they imply that pH is essential for cultivating oyster mushrooms.

2.2. Practical Environmental Fungi Cultivation Factors

The optimal environmental conditions for growing Indian oyster mushrooms depend on the strain of mushrooms being cultivated. Chitra et al. [34] discovered that Pleurotus ostreatus thrived in temperatures between 20 and 30 degrees Celsius and humidity between 55 and 80 percent. Hemalatha et al. [47] discovered that Pleurotus pulmonarius grew best on paddy straw and yielded the most when spawned for twelve months. Ragupathi et al. [48] optimized the growing conditions for various oyster and milky mushroom varieties, discovering that a temperature range of 28 to 30 degrees Celsius and a relative humidity of 70 percent worked well for oyster mushrooms. Tesfaw et al. [33] evaluated locally accessible substrates and materials for cultivating oyster mushrooms and discovered that wastepaper and gabi wastes produced more mushrooms than other substrates. Overall, the previous studies suggested that the optimal environmental conditions for growing Indian oyster mushrooms depend on the strain of mushrooms being cultivated and the availability of local substrates and materials. During the incubation period in Malaysia, the ideal temperature and humidity for cultivating oyster mushrooms are 27.4 to 29.8 degrees Celsius and 85.1 to 89.3 percent relative humidity [48]. During the phase of fruiting body formation, the temperature was 25 degrees Celsius and the light intensity was 200 lux [49]. In mushroom cultivation, DHT22 sensors detect temperature and humidity [50,51]. Environmental conditioning of mushroom houses by misting or spraying water three to four times daily may not be effective at maintaining optimal temperature and humidity [50]. The study by Chitra et al. [34] determined that the optimal oyster mushroom variety for the climate of Tiruchirapalli can be grown at temperatures between 20 and 30 degrees Celsius and relative humidity between 55 and 80 percent for six to eight months per year. IoT-based temperature and humidity control systems can help maintain optimal conditions for oyster mushroom cultivation [51,52,53]. The optimal pH range for nutrient uptake by Indian oyster mushrooms is between 5.5 and 6.5. According to Ibekwe et al. [54], the optimal mycelial yield is achieved at a pH of 6.5. The optimal pH level for oyster mushroom growth, as determined by Sultana et al. [55], is 5.5%. In addition, Jafri et al. [56] discovered that chemically treated oyster mushrooms stored in modified atmosphere packaging with 10% O₂ and 5% CO₂ maintained their quality characteristics, including nutrient content, for up to 25 days longer than untreated mushrooms. Dunkwal and Jood [57] discovered that the nutrient composition of oyster mushrooms varied based on the substrate used, but they did not directly address the optimal pH range for nutrient uptake.

2.3. Separation of Concerns for Fungi Cultivation Framework Design

This separation of concerns approach ensures that each component of the framework for fungal cultivation receives dedicated attention, resulting in a more organized, scalable, and efficient system. Separation of concerns refers to a fundamental principle in software design that emphasizes breaking down a complex system into distinct and independent parts. Each concern is responsible for a specific functionality, data group, and layer [58]. As depicted in Figure 2, this modular design increases flexibility, enables focused development and maintenance, and enables future enhancements to individual modules without system interference. To design an innovative framework for fungal cultivation using separation of concerns, the proposed framework included eight concerns: modular design, environmental control module, data monitoring and analytics module, renewable energy integration module, growth optimization module, user interface and control module, and cross-module communication. Each module addresses a specific functional aspect of fungal cultivation.

Modular design (MD) divides the framework for fungal cultivation into distinct modules, each addressing a specific aspect of the system for fungal cultivation. For instance, the framework could include modules dedicated to environmental control, data monitoring, energy management, and growth optimization. This separation of concerns ensures that each module focuses on its designated task without overlapping or interfering with others.

Environmental control module (ECM) manages temperature, humidity, and exposure to light. The module integrates IoT-based sensors and actuators to monitor and control environmental conditions [59]. By isolating this concern, the component guarantees that the cultivation environment is optimized for mushroom growth without interfering with other functions.

The data monitoring and analytics module (DM-AM) collects and analyzes data from various sensors and sources. This module can provide real-time insights into growth patterns, energy consumption patterns, and environmental alterations [60]. This separate concern enables data-driven decision-making and improved resource management.

The renewable energy integration module (REIM) is solely concerned with renewable energy integration. This unit covers solar panels, energy storage systems, and energy-efficient technologies. By isolating energy-related issues, cultivators can develop strategies to maximize the use of renewable sources and reduce the system’s carbon footprint.

The growth optimization module (GOM) optimizes growth conditions using data analytics and machine learning algorithms. This separation ensures that the cultivation process is continuously enhanced based on historical data and predictive modeling, thereby increasing yield and quality.

The user interface and control module (UI-CM) provides the interface through which system users interact. It could be an intuitive dashboard that allows growers to monitor conditions, modify settings, and receive alerts. Separating this concern makes the user experience more intuitive and effective.

While each module has its own concerns, they must effectively communicate. Cross-module communication (CMC) implements well-defined application programming interfaces (APIs) to exchange data between modules. Thus, concerns remain distinct while collaborating effectively.

2.4. Experimental Design and Setup

In the quest to realize an IoT-based fungi framework system innovation, a meticulously designed experimental setup is the foundation upon which groundbreaking insights are constructed. This section provides a comprehensive overview of the experimental architecture, hardware and software considerations, system workflow, and hardware connections that facilitate seamless data flow and analysis.

2.4.1. System Architecture Design

This architecture exemplifies the compatibility between the IoT and fungi cultivation and reveals sensor nodes strategically placed within the cultivation environment, gateways for data aggregation, data storage, and analytics platforms. The mushroom cultivation system’s architecture is intended to incorporate microcontrollers, devices, sensors, actuators, storage, and a visualization tool. The proposed system creates an automated and environmentally controlled mushroom cultivation system suitable for growth and real-time monitoring and control. The system consists of humidity and temperature sensors to monitor the air environment and a photovoltaic panel as the data receiver and power source. The Raspberry Pi gathers sensor data using Telegraf, stores it in InfluxDB, and visualizes it through Grafana. When conditions fall below a certain threshold, the system verifies the data and activates the display unit (relay and solenoid valves) to adjust the relative humidity and temperature. This architecture not only collects real-time data from sensors that monitor variables such as temperature, humidity, and energy consumption but also enables the bidirectional flow of instructions to actuators that manage controlled environments. This integrated system provides an optimal environment for mushroom cultivation, real-time monitoring, and automatic control via input and output units. These are some architectural elements:

• Input units: An input unit is a humidity and temperature sensor (AM2305B). This sensor can measure the humidity and temperature of the environment in which mushrooms are grown. Photovoltaic (PV) power stations provide the system’s energy. Solar power generation is not an IoT-based sensor. Nevertheless, the PV station plays a crucial role as an input unit, providing power to the entire system.
• Collection and storage units: The Telegraf software version 1.28 operates on the Raspberry Pi platform, facilitating data acquisition from diverse sources, encompassing sensors that measure humidity and temperature. The HTTP service is responsible for gathering the sensor readings and organizing the data in a manner suitable for subsequent analysis. InfluxDB operates in conjunction with Telegraf. The Telegraf service transmits the gathered data, which are stored in a time-series format, to the InfluxDB database. InfluxDB is responsible for the organization and storage of data, facilitating their subsequent retrieval and analysis.
• Data visualization: Grafana establishes a connection with InfluxDB to access and retrieve data that have been stored within the database. Visual dashboards are designed to present real-time and historical data obtained from sensors measuring humidity and temperature. The implementation of a dashboard facilitates the remote monitoring of the environment via a communication device, such as a smartphone or an LCD monitor.
• Control and output units: The Raspberry Pi can effectively utilize environmental criteria to monitor the data on humidity and temperature collected by the sensor. The established criteria are utilized to assess the present environment concerning predetermined standards to ascertain the necessary modifications. Suppose the environmental conditions fall below a predetermined threshold. In that case, the Raspberry Pi will transmit instructions to the display, encompassing relays and solenoid valves, intending to initiate the operation of the fog machine. The regulating process will elevate the humidity to the predetermined level. When the environmental conditions meet the prescribed criteria, the Raspberry Pi will execute a command to deactivate the fogger.

2.4.2. Hardware and Software Concerns

The foundation of this setup is comprised of meticulously selected hardware components. Advanced sensors with the capacity to detect minute variations in environmental conditions play a crucial role. These sensors communicate wirelessly with gateways that aggregate data for analysis. Actuators respond concurrently to instructions from the cloud-based analytics platform, regulating growth-critical parameters for fungi. A complex software ecosystem is implemented to facilitate this orchestration, consisting of sensor interfacing protocols, data encryption mechanisms to ensure data security, cloud APIs for data transfer, and analytics algorithms to derive insightful conclusions.

Table 1. Hardware components of this study.

Devices	Images
Raspberry Pi 4 Model B kit with memory card
Relay 12 V 1 channel Active High/Low 12 V
Solenoid Valve 4 shares 24 VDC 1/2” size 1/2 inch
Humidity and Temperature sensor AM2305B
PV station Solar panel 12 V 60 W + dry battery 12 V 12 A × 2 stations
LCD 3.3 V LCD 16 × 2 1602 3.3 V 16 Character 2 Line LCD
Mist spray set

presents a comprehensive overview of the IoT-enabled hardware in developing a system that facilitates the automatic spraying of water for equipment sustainability.

• The Raspberry Pi 4 Model B serves as the system’s central control unit. The microcontroller is responsible for executing the requisite software and establishing connections between diverse sensors and actuators, enabling the monitoring and regulating of the mushroom cultivation environment.
• The AM2305B sensor is utilized to continuously measure humidity and temperature levels in the environment of mushroom cultivation. The sensors transmit data to the Raspberry Pi for examination and analysis.
• The Solenoid Valve and Fog Mist Spray Nozzle regulate the flow of water. The mist nozzle disperses a fine water mist onto the farmland to facilitate the maintenance of optimal moisture levels required for the cultivation of mushrooms.
• Photovoltaic stations harness solar energy to provide power to the system. This sustainable energy source guarantees the system’s functionality even in geographically isolated regions lacking a reliable power infrastructure.
• The relay controls the power supply to various system components, such as solenoid valves and fogging heads, by responding to signals received from the Raspberry Pi.
• Data storage and visualization are also facilitated by using Telegraf, InfluxDB, and Grafana. Telegraf is an agent that operates on an open-source framework, facilitating the collection and transmission of data from diverse origins, such as sensors. These data are subsequently directed toward the InfluxDB database. InfluxDB is a time-series database designed to facilitate storing and managing data collected from sensors, thereby enabling efficient data storage and retrieval processes. Grafana is a data visualization tool that establishes a connection with the InfluxDB database, enabling the creation of interactive and adaptable dashboards for real-time monitoring within the context of mushroom farming environments.
• The LCD monitor or smartphone display provides real-time information about variables such as temperature, humidity, and system status. The ability to monitor conditions within the farmland is readily accessible to users.

2.4.3. Practical System Workflow

The system workflow delineates the various processes involved in the proposed IoT-based mushroom cultivation system, as depicted in Figure 3. Collecting environmental data by the humidity and temperature sensor facilitates the transmission of information to the Raspberry Pi. Raspberry Pi then utilizes these data to assess whether any modifications are necessary to uphold the most favorable conditions. The Raspberry Pi regulates humidity by operating a solenoid valve and a misting head. The relay is responsible for regulating the power supply to the various components. The Telegraf software application gathers sensor data, which are subsequently transmitted to InfluxDB for storage. Grafana facilitates the generation of visual dashboards by leveraging data stored in InfluxDB, enabling users to monitor their agricultural surroundings remotely. An LCD display is situated in front of the plantation, providing information regarding temperature and humidity.

2.4.4. Practical System Hardware Connection

The Raspberry Pi is a central controller that establishes a connection with a power source, such as a photovoltaic power station or a stabilized power supply. A relay regulates high-power devices, such as solenoid valves, using a low-power control signal originating from the Raspberry Pi. This study examines the utilization of a relay to reduce the alternating current (AC) voltage of 240 V to a lower direct current (DC) voltage of 12 V, which is deemed appropriate for the operation of the solenoid valve. The solenoid valve regulates the water flow directed toward the mist nozzle. This system configuration enables the automatic adjustment of humidity levels through spraying mechanisms. The temperature and humidity levels in the growing area are measured by humidity and temperature sensors. Additionally, the humidity level in the cultivated area is regulated by a water mist nozzle, as depicted in Figure 4.

The proposed system for mushroom cultivation, which incorporates IoT technology, comprises three main components: an experimental setup and design, the collection of data and measurement of variables, and statistical analysis techniques. The subsequent phases encompass a comprehensive architectural design of an IoT framework utilizing both hardware and software components. The architectural framework comprises input units, processing units, and output units. This study includes the provision of both hardware and software components. The research assessment of the proposed system encompassed the examination of mushroom production, the analysis of environmental information reports, and the evaluation of energy consumption and efficiency within the IoT-enabled cultivation system. Moreover, a PV station has been established to promote energy-efficient and environmentally friendly development. The installation of solar panels on rooftops generates 18 VDC from the sun. The PV station regulates electricity via a charger controller connecting to a battery that directly powers a Raspberry Pi from the PV system charger. USB ports on the solar charge controller allow the Raspberry Pi to be powered by an inverter and other components with 5 VDC 2 Ah.

2.4.5. Algorithm of Automatic Environmental Information Monitor and Controlling

The proposed algorithm monitors humidity and temperature-controlling fog-spray irrigation to maintain relative humidity in mushroom cultivation. The system incorporates a water- and humidity-resistant AM2305B sensor, Raspberry Pi 4 relays, and a solenoid valve. The algorithm begins by importing required libraries, such as the ‘time’ module for handling time-related functions and the ‘AM2305B_sensor_library’ designed for interacting with the AM2305B sensor. Key input parameters such as Wi-Fi SSID and password, server information, and sensor type (AM2305B) are variables. In addition, the system initializes output variables that can store Wi-Fi status, database access status, sensor functionality, humidity, and temperature readings. The algorithm also verifies the provided SSID and password Wi-Fi credentials, which are at least eight characters long (Algorithm 1).

Algorithm 1: Algorithm for automatic environmental information monitor and control of AM2305B humidity sensors and monitor temperature sensors.

Input: wifi_ssid, wifi_pwd, server_name, dbname, username, dbpwd, sensor

Output: wifi_status, db_status, sensor_status, humidity, temperature,

Procedure:

# Import necessary libraries

import time

import AM2305B_sensor_library as sensor_lib # Import the specific sensor library

# Define input parameters

wifi_ssid = “wifi_ssid”

wifi_pwd = “wifi_password”

server_name = “server_name”

dbname = “database_name”

username = “username”

dbpwd = “db_password”

sensor = “AM2305B” # Specify the type of sensor

# Define output variables

wifi_status = None

db_status = None

sensor_status = None

humidity = None

temperature = None

# Procedure

try:

# Validate Wi-Fi credentials

if len(wifi_ssid) >= 8 and len(wifi_pwd) >= 8:

wifi_status = “Valid”

else:

wifi_status = “Invalid”

# Validate database information

if (len(server_name) > 0) and (len(dbname) > 0) and

(len(username) > 0) and (len(dbpwd) > 0):

db_status = “Connected”

else:

db_status = “Connection Error”

# Initialize the AM2305B sensor

sensor = sensor_lib.initialize(sensor)

relay_pin = 4 #Define the relay pin

# Define threshold values

humidity_high = 92 #High threshold of humidity

humidity_low = 85 #Low threshold of humidity

temperature_high = 30 #High threshold of temperature

temperature_low = 25 #Low threshold of temperature

run_time = 30 # Run the loop for 30 s

# Start time for runtime measurement

start_time = time.time()

# Main loop

while True:

# Read sensor data

humidity, temperature = sensor_lib.read(sensor)

# Insert data into the database

# Database insertion code here

# Control relay based on humidity

if humidity <= humidity_low:

# Set relay high

# Relay control code here

time.sleep(run_time)

humidity, temperature = sensor_lib.read(sensor)

if humidity >= humidity_high:

# Set relay low

# Relay control code here

break

# Control relay based on temperature

if temperature > temperature_high:

# Set alert

# Alert code here

time.sleep(run_time)

humidity, temperature = sensor_lib.read(sensor)

if temperature >= temperature_low and temperature <= temperature_high:

break

# Insert data into the database

# Database insertion code here

# Delay the loop for 3 min

time.sleep(run_time * 6)

# Check sensor status

if sensor_status < 1:

# Restart Raspberry Pi

# Raspberry Pi restart code here

# Alert users through httpResponseCode

# Alert code here

# Close the database connection

# Database close code here

except Exception as e:

# Handle exceptions

print(“An error occurred:”, str(e))

Similarly, the system verifies the database connection information, including the server name, database name, username, and password. The sensor validation (AM2305B) is also initialized using the correct sensor library. The algorithm specifies the upper and lower boundaries for each parameter’s humidity and temperature thresholds. The relative humidity threshold is between 75% and 82% RH, and the temperature range is between 25 and 30 degrees Celsius. The algorithm’s core is an infinite loop (‘while True’) that repeatedly executes a series of actions. Within this loop, the system collects data from the sensor, including humidity, temperature, and timestamps, and inserts retrieved data into the database management system. By continuously monitoring humidity levels, a relay is activated when relative humidity falls below a predefined lower threshold, allowing for the maintenance of optimal environmental conditions. Also, the algorithm actively monitors temperature levels, activating an alert if the temperature exceeds the predetermined high threshold. After each iteration of the loop, the system implements a three-minute delay. After the loop completes, the algorithm evaluates the sensor’s status. If the recorded value is less than 1 (the sensor does not respond to the system), a set of procedures is initiated to reboot the Raspberry Pi, and an alert is communicated to a user via the front-end application. Finally, the algorithm ensures that the database connection is closed correctly and incorporates error-handling mechanisms to address potential problems during its execution.

2.5. Data Collection and Variables

Table 2. Data collection and variables for evaluating the effective IoT-based cultivation system.

Aspects	Data Collection	Variables	Description	Measurements
Environmental Parameters	Temperature	Temperature	Real-time ambient temperature within the cultivation environment.	°C
	Humidity	Humidity	Continuous monitoring of atmospheric humidity levels in the cultivation area.	Percentage
	Light Intensity	Light Intensity	Measurement of light intensity to assess appropriate light exposure for fungal growth.	Lux
	CO2 Levels	CO2 Levels	Tracking the concentration of carbon dioxide to maintain optimal growing conditions.	Parts per million (ppm)
	Airflow Efficiency	Airflow Efficiency	Monitoring the efficiency of air circulation and ventilation systems for proper airflow.	Binary (0 or 1)
Energy Consumption	Energy Usage	Energy Usage	Quantifying the energy consumed by system components, including IoT devices and sensors.	Kilowatt-hours (kWh)
	Renewable Energy Generation	Renewable Energy Generation	Measuring energy generated from renewable sources such as solar panels integrated into the cultivation system.	Kilowatt-hours (kWh)
Growth Parameters	Moisture Levels	Moisture Content	Monitoring moisture levels within the substrate to ensure optimal growing conditions.	Percentage
	Nutrient Concentrations	Nutrient Levels	Tracking concentrations of essential nutrients (e.g., nitrogen, phosphorus) for proper fungal growth and development.	Varied units
Growth Dynamics	Mycelial Growth Rate	Mycelial Growth Rate	Measuring the rate of mycelium expansion over a specific time period, indicating fungal growth.	Varied units/time period
	Fruiting Body Count	Fruiting Body Count	Counting the total number of fruiting bodies produced by the fungal cultivation.	Count
	Fruiting Body Size	Fruiting Body Size	Measuring dimensions (length, diameter) of individual fruiting bodies for quality assessment.	Varied units (e.g., millimeters)
User Interactions	Interface Interactions	User Interface Interactions	Tracking user interactions with the system interface for adjustments and settings.	Count
	Setting Changes	Setting Changes	Recording changes made to system settings based on user inputs and adjustments.	Count

outlines a comprehensive framework for data collection and the variables associated with an innovative IoT-based system for fungi cultivation. Several crucial parameters that collectively influence fungal organisms’ optimal growth and development are captured during the data collection process. The table explains the various aspects of system monitors and measurements for achieving efficient and sustainable agriculture. Included are the cultivation environment’s environmental conditions and energy dynamics, as well as the fungi’s intricate growth parameters and dynamics. In addition, the table depicts the interaction between users and the system’s user interface, emphasizing the significance of user inputs and environment configuration. Each data collection parameter is precisely defined, allowing for a thorough comprehension of the data variables and their corresponding units of product measurement. This comprehensive approach ensures a comprehensive understanding of the complexities involved in cultivating fungi using IoT technology, as evidenced by the precise nature of the data being collected, which is crucial to the successful implementation and optimization of the proposed system.

2.6. Statistical Analysis Techniques

In IoT-based fungi framework system innovation, data analysis and statistics are the compasses that direct us through the labyrinth of information gathered from the complex interaction of technology, science, and environmental dynamics. Descriptive statistics, time series analysis, and comparative analysis shine as beacons within this crucial phase of the research process. These techniques illuminate the complexities of the data and validate the significance and precision of our study’s results.

• Descriptive Statistics: This technique is the foundation of our analysis, providing a comprehensive snapshot of the collected data. The authors reduce the complexity of variables such as temperature, humidity, nutrient levels, mycelial growth rates, and energy consumption by utilizing mean, median, standard deviation, and range measures. By utilizing histograms, the authors can reveal the data distribution, clearly understanding the central tendencies and variations within our cultivated environment.
• Time Series Analysis: As the fungal cultivation system evolves over time, time series analysis emerges as a powerful tool for decoding the temporal dynamics influencing growth. Moving averages, exponential smoothing, and ARIMA models are utilized to decipher trends, patterns, and cyclical fluctuations. This analysis is essential for comprehending how environmental conditions, energy utilization, and fungal growth change over time, allowing us to optimize the cultivation process using these insights.
• The innovative IoT-based fungi framework demands validation against existing practices—comparative analysis steps in, enabling us to measure the transformative impact of our innovation. The authors quantify the framework’s efficiency, yield, and sustainability enhancements by comparing outcomes with traditional methods. The authors determine whether the differences observed are statistically significant through statistical tests such as t-tests or Mann–Whitney U tests, ensuring that our findings are not due to mere chance.

As stated previously, these techniques are not merely analytical tools; they are also essential for ensuring the validity, accuracy, and credibility of the results of our study as a result of rational seeds.

• Necessity: Data are abundant and intricate in the complex world of IoT-based fungi cultivation. The above methods reduce this complexity into easily digestible insights. Descriptive statistics establish a foundational understanding, time series analysis dissects temporal patterns, and comparative analysis quantifies the impact of the innovation.
• Validity: By employing statistical methods, the authors ensure that our findings are not merely coincidental fluctuations, but rather represent significant trends. Comparative analysis demonstrates that our framework is superior to conventional methods, instilling confidence in our conclusions.
• Accuracy: These methods provide objectivity to our study, reducing the influence of subjectivity and bias. Descriptive statistics provide accurate summaries, time series analysis captures fluctuations in real-time, and comparative analysis delivers empirical evidence of the accuracy of our innovation.

Data analysis and statistics are the link between unprocessed data and informed decision-making. They transform numbers into insights, providing a comprehensive view of the performance of our IoT-based fungi framework system. This study validated our findings through these methods and provided a foundation for the next generation of fungi cultivation practices based on empirical evidence.

3. Results

This study’s Section 3 thoroughly analyzes the data collected from the IoT-based fungi framework system innovation. In this section, the authors present the results of our research and describe the findings derived from integrating IoT technologies along with renewable energy sources in the cultivation of fungi. These findings shed light on this innovative approach’s influence on various cultivation parameters, including energy efficiency and environmental sustainability. Through a methodical presentation of descriptive statistics, time series analysis, and comparative evaluations, the authors intend to reveal the insights gained from the study and answer the research questions that guided our investigation. By investigating the complexities of the collected data and employing statistical analysis, the authors have a firm grasp of how the proposed system innovation has impacted the cultivation of fungi. This section details the outcomes of the employed methodology and the interpretation of the research findings, thereby contributing to the advancement of agricultural technology-related knowledge.

3.1. Environmental Parameters

This experimental setting environment offered profound insights into how IoT-based cultivation methods could revolutionize mushroom growth compared to traditional techniques, as presented in

Table 3. Experimental setting environment.

Items	Description	Traditional Cultivation	IoT-Based Cultivation
Experimental months	June 2022	30 Days
	July 2022	31 Days
	August 2022	31 Days
	September 2022	30 Days
Mushroom growing blocks	Block produced with the same substrate	yes
	Block diameter	10 cm
	Block long	15 cm
Solar power energy	Solar panels	-	2 × 50 watts
	Solar voltage	-	18 VDC
	Charger controller	-	7 Ah
	Battery	-	12 VDC 15Ah
	2 USB 5 VDC	-	5 VDC 2Ah
Frog mist spray	DC Pump	-	30 W 70 psi
Fruiting chamber and environmental concerns	Height	1.6 m
	Wide	1.5 m
	Depth	0.8 m
	Number of growing rows	10
	Number of growing columns	20
	Irrigation time per day Humidity recording Temperature recording	4 times (07.00, 11.00, 14.00, 17.00)	Automated system checking and data recording every 1 min
	Humidity (RH)	No controlling	Active at 85% Stop at 92%
	Temperature (°C)	No controlling	25–30 °C
	Light	Natural light intensity
	Natural water pH	7.1
	Natural Air flow	8–12 km/h

. This study sought to uncover the potential advantages of integrating technology into agricultural practices by systematically controlling and monitoring vital parameters. The ensuing sections of this research work will delve into the specific findings and outcomes of this extensive experiment, providing detailed insights into yield, quality, energy consumption, environmental impact, and economic considerations.

A comprehensive information experiment was undertaken to gauge the influence of IoT-based cultivation compared to traditional methods over four months, spanning from June 2022 to September 2022. In this study, mushrooms were cultivated using standardized growth blocks, each with a diameter of 10 cm and a length of 15 cm. The cultivation environment, crucial to the experiment’s outcomes, featured a fruiting chamber measuring 1.6 m in height, 1.5 m in width, and 0.8 m in depth. This chamber was meticulously organized with ten growing rows and twenty growing columns to facilitate systematic data collection. In the traditional cultivation approach, irrigation was manually managed with four daily checks at specified intervals. Humidity (Relative Humidity—RH) and temperature (in degrees Celsius) were monitored without active control, reflecting natural fluctuations. Humidity levels varied naturally, while temperatures ranged between 25 °C to 30 °C. Natural light served as the primary source of illumination. Conversely, the IoT-based cultivation system marked a shift in environmental management. Automated cultivation systems conducted minute-by-minute checks, providing real-time insights into humidity and temperature. The system maintained humidity levels consistently between 85% and 92% RH as well as regulated temperature within the specified 25 °C–30 °C range. An additional benefit was the system’s capability to efficiently manage irrigation, adapting to the evolving needs of the growing mushrooms. Water pH remained natural at 7.1 in both setups and air quality was determined by natural airflow, averaging between 8 to 12 km per hour (km/h).

In our study, as depicted in Figure 5, the authors evaluated the impact of mushroom cultivation in an open-air, outdoor environment, as opposed to the more controlled indoor conditions typically employed in mushroom farming. In the experimental setup, mushrooms were grown in an outdoor fruiting chamber. Unlike the indoor environment, the outdoor setup was subject to natural fluctuations in environmental conditions, including temperature, humidity, and light. The conditions were intended to simulate a less controlled, more realistic mushroom cultivation scenario. During the experiment’s several-month duration, the authors closely monitored the mushrooms’ growth in the open air. Our observations and data collection included tracking temperature, humidity, natural light intensity, and airflow variations. The parameters were systematically measured and subsequently recorded within the database system at consistent intervals. The open-air fruiting chamber allowed us to determine how mushrooms respond to the challenges of varying weather conditions and the absence of controlled indoor environments. The findings shed light on the adaptability of mushrooms to less controlled environments and provide insight into the viability of outdoor mushroom cultivation, having implications for both conventional and IoT-based cultivation techniques.

The actual growth and development of mushrooms within the fruiting chamber is depicted in Figure 6, which illustrates one of the most crucial aspects of our study. The diagram depicts the outcomes of our experimental cultivation techniques in conventional and IoT-based environments. The illustration depicts a photograph taken within the fruiting chamber at the peak of the cultivation period, displaying a close-up of the mushroom’s consistent growth blocks within the chamber and emphasizing its robust and healthy development. This visual evidence demonstrates the viability and vitality of the method of mushroom cultivation utilized in this study. The fully developed mushrooms in the fruiting chamber indicate that the experiment’s environmental conditions were adequate. This study result demonstrates the practical adaptability of mushrooms to real-world environments, which is crucial when considering the scalability and adaptability of cultivation techniques. This study analyzed yield, quality, and the impact of IoT integration and solar renewable energy sources on mushroom growth. The experimental result provided evidence to complement quantitative data for a comprehensive understanding of the success of mushroom cultivation in the fruiting chamber.

Figure 7 depicts a fully matured Indian oyster mushroom ready to be harvested in the early morning hours. The mushroom, meticulously grown in the fruiting chamber under controlled conditions, demonstrates the effectiveness of applying IoT technologies along with solar renewable energy sources. The positive impact on mushroom cultivation practices can support agricultural endeavors in terms of yield and quality, as well as their scalability potential.

3.2. Analysis of Validity and Efficiency in the IoT-Enabled Cultivation System

Validity and efficiency assessments are crucial in IoT-enabled agriculture because they reveal the actual effects of this cutting-edge technique. A rigorous t-test analysis was conducted to confirm the efficiency of the system. This analysis served as a statistically sound instrument for identifying critical differences between traditional mushroom cultivation techniques and the IoT-based system. In addition, the effectiveness of the Internet of Things-enabled cultivation system was rigorously evaluated by comparing mushroom growth and harvest information. Considering the period from June to September 2022, the results compare the two systems to determine how well they performed and adapted to weather changes. This method provides a concrete and valuable measure of the efficiency of the IoT-enabled cultivation system by quantifying the weekly yields of harvested mushrooms in kilograms. The analysis results emphasize the theoretical contributions of this investigation and provide practical implications, delivering a solid foundation upon which to construct a more comprehensive understanding of this revolutionary green agricultural paradigm. Figure 8 shows a graphical indication of the performance of traditional mushroom cultivation over time, as measured by weighted yield results. A linear regression equation was used to construct the meaning of the data as a whole, resulting in the impressive equation y = −0.0731x + 4.7554 with an R² of 0.9917. In this equation, ‘x’ represents time, and more specifically, the week of the month, whereas ‘y’ represents the yield of mushrooms. The negative coefficient (−0.0731) indicates a decreasing trend in mushroom yield over time, implying a slight weekly decline in yield on average. The intercept represents a yield estimate of approximately 4.7554 kg at the beginning of the observation period. The statistical measure known as the coefficient of determination (R²) indicates how well the regression model matches the data.

Time and mushroom yield have a strong linear relationship (R² = 0.9917). This indicates that the regression equation adequately captures the observed variations in yield, making it a valuable tool for forecasting mushroom production month-by-week. These quantitative results explain the dynamics of conventional mushroom cultivation and demonstrate how crucial time-related factors are for optimizing yields. The regression analysis is strengthened by the time series data presented in the preceding table, which demonstrate yield fluctuations consistent with the equation’s interpretation. The subsequent sections will delve more deeply into the practical implications, limitations, and areas for future research.

Figure 9 depicts the weight yield of mushrooms cultivated with IoT-based cultivation along with solar renewable energy integration. The time series analysis of the data produced a significant coefficient of determination (R²) value of 0.9917, and the equation y = −0.0731x + 4.7554. By solving this equation, we can determine how the IoT-based cultivation system affects mushroom yield in the long run. In calendar weeks, the mushroom harvest (represented by ‘y’) is correlated with time (represented by ‘x’). The negative coefficient (−0.0731) indicates a weekly decline in mushroom yield. The result suggests that the yield gradually decreases over each month. The equation’s intercept, equal to 4.7554 kg at the start of the observation period, can be used to calculate an initial yield estimate. This value represents the baseline yield and provides context for subsequent yield changes. The R² value of 0.9917 indicates that the regression model is a good fit for the data, indicating a strong linear relationship between time and mushroom yield. The regression equation captures yield trends and variations over the observation period.

Figure 10 presents a comparative analysis between applying IoT-based and traditional methods of Indian oyster mushroom cultivation. The study examines the yield of mushrooms in terms of weight over several months. Based on the empirical evidence, the results show that mushroom cultivation employing IoT technology consistently yields more products than traditional cultivation approaches. On average, this study found that mushroom cultivation utilizing IoT technology yields approximately 28% higher mushroom production in comparison to conventional methods. The consistency of yields is of great value to mushroom cultivators seeking enhanced reliability. Just as seasonal changes influence the growth patterns of mushrooms, the productivity of both approaches is subject to environmental fluctuations. The growth potential of mushrooms increases as they mature, as evidenced by the overall increase in yield observed across both cultivation methods. The primary conclusion to be drawn is that the implementation of IoT technology in cultivation practices yields enhanced productivity and consistency. This development holds significant transformative potential for mushroom farming, amplifying agricultural output and profitability.

The primary focus of this study is to assess the practical impact of the implemented system innovation by examining the validity and efficiency of the IoT-enabled cultivation system along with solar renewal energy. According to the t-test analysis, the findings offer significant insights into the differences observed between conventional methods of cultivating Indian oyster mushrooms and an IoT-based approach. As demonstrated in

Table 4. Indian Oyster Mushroom Cultivation Difference in Applying System Innovation.

Experiment	Mean	SD	t	df	p
Traditional Cultivation	4.118	0.356746	8.1674	30	0.000
IoT-based Cultivation	5.306	0.459665

, the mean yield for traditional cultivation is 4.118 kg, with a standard deviation of approximately 0.3567. Simultaneously, the IoT-based cultivation system demonstrates a notably higher average yield of 5.306 kg, accompanied by a standard deviation of approximately 0.4597. The presence of significant disparities is highlighted by the t-test statistic, which yields a value of 8.1674 with 30 degrees of freedom, thus emphasizing the statistical significance of the observed differences. Implementing the IoT-based cultivation system obviously impacts these variances, as demonstrated by the p-value of 0.0000, which is crucial in proving that they are not random variations. The findings presented in this study significantly contribute to the theoretical framework of IoT-based cultivation and provide empirical support for its practical applications. In addition, these findings have important practical implications for individuals involved in mushroom cultivation, as they underscore the potential benefits of implementing this novel system. Specifically, applying this innovative approach has resulted in significantly increased yields, thereby improving the economic feasibility of mushroom farming. Nevertheless, it is imperative to recognize the specific constraints of the study and possible avenues for future research, which will be elaborated on in the subsequent sections.

In Figure 11, the dynamics of the solar-powered IoT-based cultivation system’s electricity consumption are analyzed in compelling detail. Over four months, the IoT-based mushroom cultivation system consumed 30 kWh for overall system activities. This transition is noteworthy because it coincides with a substantial reduction in carbon emissions. In June, the system utilized 7.38 kWh of solar energy, which reduced carbon dioxide emissions by 6.27 kg. In July and August, the trend of increased solar energy use and a 7.04 kg per month decrease in carbon emissions continued. Even though the growing season ended in September, the system still collected 7.43 kWh of solar energy and released 6.32 kg of carbon dioxide. These results demonstrate how using solar renewable energy sources in agriculture, such as solar power, can benefit the environment and reduce carbon emissions. The research demonstrates that solar energy can be a sustainable alternative to conventional grid electricity without sacrificing efficiency or usability. This study demonstrates significant reductions in carbon emissions, lending credence to the use of solar renewable energy sources in agriculture and aiding in achieving sustainability goals. These results demonstrate the economic and environmental advantages of utilizing less conventional energy and adopting more sustainable practices, in line with the worldwide interest in greener agricultural systems.

3.3. Comparison of Indian Oyster Mushroom Growth and Economic Market Analysis

The authors compare and contrast the growth dynamics of Indian oyster mushrooms grown using traditional methods and a system based on the IoT. The evaluation results also determine the economic viability of endeavors dependent on mushroom yield and quality. The comparison is based on empirical data collected over a long period of time, which meticulously tracked the growth parameters and characteristics of Indian oyster mushrooms under both cultivation techniques. By analyzing variables such as growth rate, size, weight, and overall quality, this technique yields profound insights into the effect of IoT integration with solar renewable energy use on mushroom cultivation. In addition, a thorough market analysis is conducted to investigate the economic aspects of IoT-based cultivation techniques. Farmers, agricultural practitioners, and policymakers can gain valuable insights from the findings’ holistic perspective on the future of mushroom cultivation.

Figure 12 depicts the development of Indian oyster mushrooms from their earliest stages, spanning the first and second days of growth, to their eventual harvest. This captivating illustration captures the remarkable transformation of these mushrooms throughout the mushroom cultivation process. The figure depicts the stark contrast in size, color, and overall appearance between the early growth stages and the final harvest. The visual narrative provides a profound understanding of the potential of the IoT-based cultivation system, emphasizing its capacity to foster and optimize mushroom growth, thereby increasing yield and quality. The progression from initial growth to market-ready produce exemplifies the efficacy of our innovative approach, which has the potential to revolutionize mushroom farming techniques.

Figure 13 depicts a comparative visual analysis of the growth trajectory of a single Indian oyster mushroom, contrasting the results of IoT-based cultivation with conventional methods. The comparison highlights the substantial differences in size, coloration, stem thickness, and weight. In the IoT-based cultivation system, a single mushroom grows to approximately 5.5 × 12.2 cm with a slightly darker hue, a thicker stem, and a heavier weight. In contrast, the traditionally cultivated counterpart is 4.5 × 9.0 cm in size and possesses distinct characteristics. This persuasive visual evidence demonstrates the transformative potential of IoT-based cultivation for enhancing the growth and quality of individual mushrooms. Observed differences in size and physical characteristics prove the system’s effectiveness in optimizing environmental conditions and resource utilization. These advancements significantly impact mushroom farmers, as they promise greater yields of larger, healthier mushrooms. The figure comparison highlights the tangible advantages of adopting IoT-based techniques in mushroom cultivation and provides a glimpse into the future of agricultural practices.

Figure 14 depicts a mushroom cluster measuring approximately 14 × 16 cm. The mushroom cluster on the left was grown traditionally and weighed approximately 30.15 g. On the other hand, the mushroom cluster on the right side of the image was grown using an IoT-based cultivation system and weighed approximately 40.21 g. The mushroom cluster produced by the IoT-based cultivation system was 25.02% heavier than those produced by conventional cultivation. The color of mushrooms grown using an IoT-based cultivation system was noticeably darker, and they were stiffer, thicker, harder, and more complete than those grown using conventional cultivation techniques. Considering the current market environment, these findings are of immense significance. Implications are far-reaching in the context of Indian oyster mushrooms, which command an approximate market price of $2.5 per kilogram. Our IoT-based cultivation system yields mushroom clusters capable of producing up to 80 g per block, demonstrating its potential. This study not only forecasts an improvement in the quality and quantity of produce but also in measurable economic benefits for cultivators, potentially redefining the mushroom farming landscape.

4. Discussion

Comparing and contrasting the proposed IoT-enabled cultivation system with conventional methods reveals several noteworthy aspects, especially regarding growth and economic market analysis, validity and efficiency, and environmental sustainability. The IoT-enabled cultivation system demonstrates an evident growth and economic market analysis advantage. Through precise environmental control and real-time data collection, an IoT-based approach consistently produces mushrooms of higher quality, as evidenced by their increased size, improved appearance, and increased weight. As the market favors superior produce, IoT cultivation systems increase farmers’ economic returns. On the other hand, traditional methods are inadequate to achieve this level of precision, resulting in inconsistent and frequently inferior yields. The IoT-enabled system is also substantially better in terms of validity and efficiency. Using data analytics and real-time monitoring, the system ensures that cultivation parameters remain within optimal ranges, thereby decreasing the probability of errors and resource waste. The IoT-based strategy improves the overall productivity of mushroom cultivation by reducing resource consumption and waste. Traditional methods are more susceptible to inefficiency and human error, negatively impacting yield and resource management.

Nonetheless, this study is essential and identifies certain contradictions and obstacles associated with the IoT-based approach. For smaller-scale mushroom farmers, the initial setup cost, including integrating Internet of Things technologies and solar renewable energy sources, can be a significant barrier. Traditional methods, in contrast, are typically more financially accessible upfront. Moreover, the IoT-enabled system excels in efficiency and accuracy, and its installation and ongoing management require higher technical expertise. Traditional methods, which rely on conventional agricultural practices, may be more accessible to a greater number of farmers with varying degrees of technological fluency. The IoT-enabled system’s reliance on solar renewable energy sources is consistent with eco-friendly practices in terms of environmental sustainability. However, for a comprehensive sustainability assessment, the production and disposal of IoT hardware components may have environmental implications that must be considered. Traditional methods, despite being less energy-efficient, may not involve these issues.

Traditional mushroom cultivators frequently employ shade netting to reduce direct sunlight exposure, insulation to maintain cooler temperatures, and controlled environment systems, such as air conditioning and humidity control, to create more favorable conditions for mushroom growth. These measures aim to balance the challenges of heat optimization for mushroom cultivation but the problems of remote real-time environmental information monitoring still exist. The proposed IoT-based approach represents the potential for precision agriculture to revolutionize mushroom farming practices, providing increased productivity, sustainability, and adaptability in the face of consistent and stable environmental conditions. The IoT-integrated strategy, enabled by real-time monitoring and control, demonstrated a distinct yield and quality metrics advantage. This result is consistent with previous research [19,20,21,22] emphasizing the significance of precise environmental control for optimizing crop production. In this study, the experimental cultivation of Indian oyster mushrooms was conducted in Thailand, a tropical nation in Southeast Asia. Therefore, the controlled humidity threshold is between 75% and 82% RH, and the temperature is between 25 °C and 30 °C. The IoT-enabled system ensured that key growth parameters such as temperature, humidity, light, and irrigation time were consistently maintained within optimal ranges, resulting in larger mushroom sizes, enhanced uniformity, and increased yield. Numerous studies have shown [22,61] and our results confirm that integrating IoT technologies into the mushroom cultivation process positively affects harvest productivity.

Despite the encouraging results, numerous future research and exploration avenues have emerged. While this study focused on Indian oyster mushrooms, the effects of IoT-integrated cultivation may vary for other mushroom varieties with different growth requirements, as supported by [20,62,63]. Investigating the adaptability and scalability of IoT technologies for various mushroom species could yield insightful information. In addition, the study focused primarily on the immediate impact on yield and system design simplicity. Long-term effects, such as the sustainability of mushroom farming advancements and the improved cost-effectiveness of yield and quality over multiple cultivation cycles, necessitate additional research. Exploring the interaction between IoT technology, renewable energy sources, and specific mushroom genetics could similarly yield nuanced insights into cultivation dynamics.

The reliability of the methodology utilized in this study results from the experiment’s meticulously controlled environment. Identical environmental conditions were applied to IoT-integrated and conventional cultivation systems to ensure a fair comparison. The data collection procedure minimized human error and potential bias using IoT sensors and automated monitoring stated by the previous research [64,65]. However, it is essential to note the limitations. The study was conducted in a controlled environment, so the results may vary depending on the outdoor conditions. In addition, while the IoT system provided real-time data, occasional technical errors could affect the precision of particular measurements.

Validity is supported by the study’s consistency with existing scientific literature. Prior research has established the principles of controlled environment agriculture and the impact of IoT on mushroom harvest production [19,22,40,61]. Positive results observed confirmed the validity of the formulated research questions. In addition, the validity of the methodology is enhanced by its systematic approach to data collection, statistical analysis, and comparison. The statistical significance of the results validates the study’s conclusion that IoT-integrated mushroom cultivation method is superior in terms of yield, mushroom cultivation improvement, and energy conservation. The innovation in the green cultivation system aligns with the global shift toward precision agriculture, where data-driven decisions allow for more efficient resource utilization. Additionally, the study highlights the potential for incorporating solar renewable energy sources, not only for environmental sustainability but also for enhanced economic viability.

The energy consumption and efficiency analysis within the IoT-enabled cultivation system innovation has yielded invaluable insights into the sustainability and potential environmental benefits of integrating modern technologies into mushroom farming practices. The results indicate that the IoT-enabled system innovation with solar renewable energy reduced energy consumption significantly compared to conventional IoT-enabled methods. This result validates the initial objective that the control of mushroom farming enabled by IoT-integrated solar renewable energy should lead to optimized resource utilization, ultimately resulting in energy savings. The increased energy efficiency exhibited by the IoT-enabled system innovation is a significant step toward environmentally sustainable and conservative agricultural practices.

The data on energy consumption were collected using precise measurement instruments, thereby minimizing error. However, the dependability may be compromised by factors such as sensor calibration and potential power supply fluctuations. The methodology is valid because the experiment adheres to the principles of agricultural energy analysis. The study’s outcomes are consistent with the existing understanding that precision control through IoT technologies can lead to energy savings [23,24,25,26,66,67]. The statistical significance of the results strengthens the credibility of the drawn conclusions.

The cost of implementing an IoT-enabled cultivation system can vary significantly based on the hardware selected, specifically the Raspberry Pi system. Utilizing Raspberry Pi Zero, which offers cost-effective functionality, can incur a minimum expense of approximately USD 130. However, this study utilized a Raspberry Pi 4 system, resulting in a slightly higher system cost of approximately USD 200. This system’s payback period highly depends on the initial investment and the number of mushroom blocks under cultivation. In this particular research scenario, with approximately 200 mushroom blocks in operation and an average yield of approximately 5 kg per week, each yielding an estimated USD 2.5 per kilogram, the system is anticipated to achieve payback in a relatively brief period of approximately 16 weeks. The total yield from the IoT-based cultivation system corresponds to approximately 80 kg of mushrooms over the specified time period. It is essential to note that the payback period can vary significantly depending on factors such as the size of mushroom blocks, market conditions, growing seasons, climate, and resource costs. Individualized optimizing cost–benefit analyses are required for particular implementations.

The energy efficiency demonstrated by the sustainability of IoT-enabled mushroom cultivation offers practical benefits, such as lower operational costs for farmers. The decreased energy consumption is consistent with global sustainability goals and contributes to a greener and more environmentally conscious agricultural sector. Moreover, the positive correlation between IoT integration and energy efficiency emphasizes the significance of investing in resource-optimizing technologies. This research is consistent with the growing trend toward precision agriculture, in which data-driven decision-making minimizes waste and maximizes efficiency.

5. Conclusions

This study highlights the transformative potential of IoT-integrated and solar renewable energy-driven mushroom cultivation techniques. From empirical observations to theoretical contributions, the research not only addresses the research questions but also has practical implications for the agricultural landscape. By embracing innovation, technology, and environmental responsibility, this study propels the conclusion on modern agriculture into a realm where IoT and solar renewable energy serve as catalysts for a resilient and adaptable agricultural future.

5.1. Theoretical Contributions

This study investigates the potential synergistic integration of IoT technologies and solar renewable energy sources in the context of mushroom cultivation, with a focus on Indian oyster mushrooms. This study highlights the significant effects of incorporating modern technology and renewable energy into conventional agricultural practices. In order to conclude, a thorough examination of theoretical advancements, practical consequences, constraints, and potential future developments is conducted. This study offers empirical evidence of the pragmatic benefits of applying IoT technologies with renewable energy sources. The design addresses the fundamental question of the effect of this integration on the yield and quality of mushrooms compared to conventional cultivation methods and reveals positive results. The findings demonstrate the potential for technology-driven cultivation to improve agricultural productivity and address the challenges of scalability and adaptability in the context of IoT-integrated and renewable energy-driven cultivation techniques. These results demonstrate the transformative nature of such methods. The empirical evidence supports the scalability and adaptability of these techniques as they demonstrate their potential to alter agricultural practices. This pragmatic implementation allows farmers to formulate sustainable food production strategies. Understanding the technical challenges and implementation considerations associated with applying IoT systems along with renewable energy sources within the context of mushroom farming practices contributes to an all-encompassing comprehension of the innovation process. The results shed light on this integration’s technical and data synchronization difficulties. These insights provide professionals with valuable assistance in overcoming obstacles and making informed decisions. This study demonstrates the potential yield and quality benefits of applying IoT technology and renewable energy sources to mushroom cultivation practices. According to the evidence, the integration process can potentially increase harvest yield and quality. The theoretical contribution is intended to increase agricultural productivity and strengthen food security.

5.2. Practical Implications

This research has wide-ranging agricultural implications. Integrating IoT technology and solar renewable energy sources can improve food safety and environmental sustainability by increasing mushroom productivity. The observed increase in crop yield and product quality suggests the potential for widespread implementation of these methodologies within the mushroom farming industry. The design has demonstrated that applying IoT systems and using renewable energy sources increases resource efficiency, thereby establishing a significant model for advancing agricultural technology to increase resilience and promote environmental consciousness. This study has practical implications for the agricultural industry. The empirical evidence suggests that the use of IoT technology and renewable energy sources has the potential to increase the yield and quality of mushroom crops and contribute to the overall improvement of environmental conditions. Empirical validation enables the pragmatic implementation of precision agriculture, facilitating beneficial and efficient food production. The research findings have significant applications in the real world. The cultivation of mushrooms is an integral part of numerous dietary practices, and the results of our investigation can improve food security. Combining IoT technology can increase the yield and quality of mushrooms, thereby contributing to mushroom production’s environmental sustainability and efficacy. This strategy has benefits for farmers and consumers who need dependable and superior green agricultural products and renewable energy sources. IoT systems and renewable energy sources have the potential to accelerate the adoption of resource-efficient and environmentally sustainable farming practices across multiple agricultural sectors.

5.3. Limitations and Future Work

This study made numerous contributions, and its limitations must be acknowledged. Validation of controlled research may be required in agriculturally relevant environments. Given the current emphasis on the Indian oyster mushroom, additional research is necessary to determine the applicability of these findings to other mushroom species and geographic regions. Given the study’s emphasis on yield and quality, it is necessary to conduct further research into this integration’s ecological and economic effects. This study offers numerous avenues for future research. Utilizing IoT technology and renewable energy, this study contributes to advancing mushroom cultivation. This study also highlights the need for additional research and exploration. While this study sheds light on IoT integration’s immediate energy consumption implications, several research gaps and opportunities remain. The analysis primarily focused on the cultivation process’s short-term energy consumption. Understanding the entire cultivation lifecycle, including pre-production and post-harvest phases, would provide a more holistic perspective on energy efficiency. In addition, a lifecycle analysis of energy use, beginning with the production of IoT components and ending with system disposal, could yield more nuanced insights. Investigating how IoT integration affects energy consumption under varying environmental conditions and for various mushroom varieties could also yield valuable information. Future research should prioritize the investigation of optimal scalability, the analysis of adaptation across diverse contexts, and the evaluation of global economic and ecological impacts. Additional research into the potential synergistic effects of emerging technologies could result in significant advances. Enhancing the technical aspects of applying the IoT and renewable energy sources while also addressing implementation-related challenges and factors has the potential to promote the development of comprehensive frameworks that can be adopted more broadly. Enhancing scalability and adaptability, increasing economic viability, and employing predictive models have the potential to revolutionize mushroom cultivation techniques.