Review of Monitoring and Control Systems Based on Internet of Things

Abstract

The Internet of Things is currently one of the fastest-growing branches of computer science. The development of 5G wireless networks and modern data transmission protocols offers excellent opportunities for rapid development in this field. The article presents an overview of monitoring and control systems based on the Internet of Things. The authors discuss various aspects of these systems, including their architecture, applications, and challenges. We focus on analyzing the latest achievements in this field, considering technological innovations and practical applications in various sectors. Also, we emphasize the importance of integrating data from multiple sources and developing data analysis algorithms to ensure the effectiveness and precision of IoT-based monitoring and control systems. The article provides a valuable overview of the current state of knowledge in this dynamic area, inspiring further research and technological development. It also includes case studies showing various IoT device applications and energy consumption management.

1. Introduction

The Internet of Things (IoT) is a technological revolution and a change in how we perceive and communicate with the world around us. This is a dynamically developing area of IT, which significantly changes everyday life by integrating an increasing number of devices and systems with the global network. They range from simple home devices, such as thermometers or humidity sensors, to advanced monitoring and control systems in industry. The IoT permeates all spheres of life, providing new opportunities and challenges [1]. In recent years, there has been a clear trend of increasing numbers of home devices equipped with IoT functions. The concept of a smart home is becoming increasingly common, where all elements—from lighting and heating to kitchen appliances and security systems—are connected into one coherent network, enabling remote management and monitoring. However, this is only the tip of the iceberg as the potential of the IoT also goes deep into industry [2,3], transport [4], healthcare [5], agriculture, and many other economic sectors [6,7]. Figure 1 summarizes typical IoT solutions.

IoT technologies use various communication protocols, from popular wireless standards such as Wi-Fi [8], Bluetooth [9], or Zigbee [10,11] to wired protocols such as Modbus [12] or CAN [13]. This diversity allows for flexible adaptation to different requirements and environments while opening doors to new possibilities and applications. In addition to the wireless mentioned above and wired standards, IoT technologies also use several other communication protocols that expand the possibilities and scope of their applications. One such important protocol is GSM [14], which enables communication between IoT devices and mobile networks. Thanks to this, devices can be remotely monitored and controlled even in places without access to Wi-Fi or Bluetooth networks. With the development of mobile technologies, the 5G standard [15,16] is also becoming increasingly important. Moreover, 5G, the fifth generation of mobile technologies, offers extremely fast data transmission speeds and low latencies, which makes it an ideal solution for the IoT applications that require high bandwidth and immediate response. Thanks to 5G, new IoT applications, such as advanced real-time monitoring systems and autonomous vehicles, become possible. Another important protocol gaining popularity on the IoT is LoRa [17,18]. LoRa is a wireless communication protocol that enables data transmission over long distances while consuming minimal energy. Thanks to this, LoRa is used in cases where it is necessary to monitor and control devices in large areas, such as when fields and farms are monitored. Figure 2 summarizes the data transmission protocol used by the IoT. This summary covers the layers of the OSI model in which these protocols operate.

However, with the IoT expansion, new challenges arise, especially in security [19]. Many manufacturers focus on bringing low-cost IoT solutions to market quickly, often at the expense of appropriate security standards. This results in serious vulnerabilities that can be exploited for unauthorized access and data leakage, compromising user privacy and security. Despite these threats, there is enormous potential in developing the IoT. In the era of the dynamic development of the concept of smart cities [20], smart energy [21], and smart agriculture [22], IoT systems are becoming a key tool that enables the optimization of resources, reducing costs, and improving the quality of life.

This article provides an in-depth review of the literature on IoT-based monitoring and control systems. Various solutions were compared to identify their advantages and disadvantages and indicate potential future development directions. The aim is to understand the current state of technology and determine a development path that will enable the maximum use of the IoT’s potential for the benefit of society and the environment.

1.1. Motivations and Contributions

Writing an article on IoT-based monitoring and management systems is an exciting challenge and a critical step in understanding and helping to shape the future of technology. The IoT is a dynamically developing field with enormous potential to transform various aspects of our lives, from smart homes and city management to advanced environmental monitoring systems. Through a detailed literature review, we can identify the current state of technology and better understand what solutions are most effective and what challenges we face. This will allow us, as a collective, to consciously shape the future of this technology to benefit society and the environment.

Analyzing the advantages and disadvantages of IoT-based monitoring and management systems is crucial to understanding which technologies are most effective in different contexts and what technical and organizational barriers must be overcome to realize their full potential. We can determine best practices by comparing solutions and indicating areas that require further research and development. Identifying future development directions will help optimize existing systems and identify innovation paths that can lead to more advanced, sustainable, and user-friendly solutions.

This paper focused on IoT-based monitoring and control systems for smart agriculture, predictive Maintenance Systems, healthcare, environmental protection, and smart cities. The article analyzes a variety of IoT-based monitoring and control systems applications, showing their significant impact on improving operational efficiency, thus reducing costs and increasing the quality of services. The purpose of writing this article is not only to document the current state of IoT technology but also to inspire further research and development of new technologies that will fully exploit the potential of the IoT. Indicating future development directions will allow us to concentrate research and investment efforts in the most promising areas, which, in the long run, will benefit not only the technology industry but, above all, the entire society and the natural environment. In this way, the article can become a valuable tool for scientists, engineers, and decision-makers who want to contribute to building a more sustainable and technologically advanced future.

1.2. Methodology

During our research, we collected articles using various search engines (mainly Google Scholar and DBLP). Moreover, we analyzed references from articles found and citations from these papers. Our goal was to compose the most complete and up-to-date review of the security of monitoring and control systems based on the IoT.

1.3. Organization

The rest of this paper is organized as follows. Section 2 presents the related works connected to this manuscript’s theme. In Section 3, we provide an overview of the monitoring and control systems based on the IoT. In Section 4, we will summarize and conclude our analysis of the discussed systems. In the Section 5, we will present the conclusions of the entire article, findings from the research, and our plans for the future.

2. Related Works

The area of monitoring and control systems based on the IoT is the subject of intensive research, reflected in numerous scientific publications. The literature contains descriptions of various monitoring and control systems based on the IoT.

Shinde et al. in [23] review IoT-based environmental monitoring systems whose main goal is to provide environmental data from remote locations via the Internet. The presented system uses low-power wireless Internet-connected sensors that transmit their measurements to a central server, enabling remote visualization and data analysis from any Internet-connected device. The developed solution is a comprehensive system covering the physical level (sensors and communication protocol) and data management and storage at the cybernetic level, improving the integration and interoperability of systems and increasing supervision efficiency.

Chakraborty et al. in [24] systematically assesses the recent literature on smart homes and reviews research and development in this field. It presents a detailed picture of the development and features of today’s smart home systems, offering deep insight into the latest hardware and trends. The article also discusses important services and their advantages, current and future research trends, and the difficulties and obstacles associated with their implementation.

Yassein et al. in [25] discuss using IoT technologies in various industries, particularly healthcare, where the IoT transforms traditional systems into intelligent healthcare systems. It presents an overview of IoT-based services, software and techniques developed in the health sector, highlighting the benefits of their implementation. The paper’s findings are intended to serve as a source of information and reference for medical professionals, researchers, and those interested in smart healthcare.

Tokognon et al. in [26] discuss the importance of the IoT (as a key technology for monitoring systems, resulting from the rapid development of sensor technologies and the convergence of information technologies. It presents a framework for structural health monitoring (SHM) using IoT technologies, considering the technologies used in implementing SHM systems and data routing strategies in the IoT environment. The article also describes big data solutions necessary to manage large and complex data generated by sensors installed on structures.

Bagdadee et al. in [27] discuss the importance of energy management in the context of the growing energy demand for IoT applications and the promotion of green industry. They present a framework for connecting reservations and increasing energy efficiency in IoT-based smart industries, covering solutions for energy generation and low-power device management. The paper also examines case studies, including energy planning in smart factories and wireless energy transfer, while discussing unresolved issues related to IoT-based energy management systems.

Al-Turjman et al. in [28] discuss the growing demand for energy production due to the expansion of population and energy consumers in large cities, highlighting the importance of energy monitoring systems as an effective solution to optimize the growing energy demand and consumption. They review and classify existing energy monitoring approaches and enabling technologies, such as sensors and portable devices, highlighting practical aspects and performance issues. It analyzes key design factors, customization parameters, and real-world use cases while presenting observed patterns and statistics in the field.

Zulkifli et al. in [29] discuss the importance of monitoring water quality in the transition to smart agriculture and the automation of monitoring key components of everyday needs such as water. Reviews the literature on water quality monitoring models, highlighting the need for accurate and complete datasets and precise modeling using sensors to collect water properties during experiments. It analyzes 50 articles from 946 collected papers, focusing on issues of model accuracy, the development of data collection systems and the types of data used, and presents directions for future research in intelligent water quality monitoring.

Jan et al. in [30] discuss the growing problem of safe water shortages caused by population growth, pollution and climate change, highlighting the importance of monitoring water quality, especially in domestic use. Reviews the shortcomings of traditional laboratory water quality testing methods and the weaknesses of wireless sensor network (WSN)-based systems regarding energy management, data security, and communications coverage. The article presents an overview of current IoT-based water quality monitoring systems, focusing on monitoring parameters and smart sensors and design recommendations for more effective systems that can benefit from developments in IoT technologies to improve water quality in-home applications.

Prapti et al. in [31] discusses the emerging field of IoT-based aquaculture, which is part of the 4.0 agriculture era but is lagging in many countries. A review of research published between May and December 2020 examines 30 international scientific papers on water quality monitoring in fish ponds. The article classifies research into five categories—latest research (2011–2020), aquaculture environments, research approaches, the most frequently monitored water quality parameters, and the forms of solutions provided—pointing to the dominance of freshwater aquaculture and the importance of parameters such as temperature and dissolved oxygen and pH in IoT monitoring systems. It also highlights the need for long-term experimental research to identify challenges and propose appropriate solutions. It highlights the importance of real-time monitoring as the most commonly used solution.

Pal et al. in [32] discuss the growing production challenges in the automotive industry and the increase in energy consumption, which lead to increased costs and greenhouse gas emissions, emphasizing the importance of efficient energy use. It presents various methods and mechanisms of energy management in a smart grid using communication technologies and protocols. It proposes the integration of electric vehicles with a smart electrical grid to charge and discharge energy and exchange information effectively. The article also discusses integration strategies, implementation of multi-agent systems to monitor energy flow and maintain grid stability, optimal scheduling of electric vehicle charging, and comparison of standard communication protocols in various scenarios.

Vaidya et al. in [33] present an overview of models of intelligent transport systems (ITS) with advanced traveller information systems (ATIS) and advanced road traffic management systems (ATMS) for intelligent transport. Describes GIS and IoT technologies in ITS, using sensors and detection algorithms worldwide. The ATIS model provides travellers with regional travel information, enabling them to make informed decisions about the best transport mode, route, time and cost. At the same time, ATMS includes real-time data management, vehicle detection and tracking, communications, variable message systems, traffic forecasting and dynamic motion control. The article discusses hardware components such as CCTV cameras, inductive loops, magnetometric, infrared, acoustic, ultrasonic, radar and GPS sensors in ATIS and ATMS systems.

Pandey et al. in [34] discuss the role of technology in agriculture, paying attention to the growing demand for food and the difficulties associated with traditional agricultural methods, such as dependence on human labour, weather variability, and lack of knowledge and technology. It presents an overview of IoT-based solutions that can increase crop productivity, covering soil and plant health monitoring, smart irrigation, and real-time weather forecasting. The article presents the IoT architecture in the smart agriculture model and a schematic model of an automated agricultural system that integrates data from various subsystems using artificial intelligence (AI) algorithms, enabling notifications to be sent to farmers’ phones and effective management of fertilizers, pesticides and water, which contributes to increased crops.

Kim et al. in [35] summarizes the application of IoT technology in agricultural automation, analyzing its implementation in various agricultural systems such as management, monitoring, control systems and unmanned machines. IoT-based communication technologies used in agriculture, such as Wi-Fi, LoRaWAN, mobile communication (2G, 3G, 4G), ZigBee and Bluetooth, were also discussed. The article points to the limitations and prospects for the development of the IoT in agriculture, emphasizing that the future development of communication technologies such as 5G will enable a broader and faster use of the IoT in various agricultural processes, which will contribute to the automation of agriculture, improving the quality and efficiency of crops and reducing the labour input.

Hirlekar et al. in [36] highlight the importance of infrastructure, especially bridges, which are key national resources and important for socio-economic development. Draws attention to the need for regular and effective auditing of bridges, which are particularly susceptible to damage and require frequent inspections, to avoid the risk of serious damage that could threaten life and property. The article discusses various techniques used in auditing the health of bridges.

Saini et al. in [37] article presents a systematic review of current knowledge about indoor air quality monitoring systems based on IoT technology. It focuses on design aspects such as types of sensors, microcontrollers, architecture, and connectivity, and it discusses problems related to the implementation of research published in 2015–2020. The review shows that 70% of studies focus on monitoring thermal comfort parameters, 65% on CO₂ levels, and 27.5% on PM levels, while 37.5% and 35% of systems are based on Arduino and Raspberry Pi controllers The article also indicates that only 22.5% of studies used calibration before system implementation, while 72.5% of systems claim energy efficiency.

Lavanya et al. in [38] discuss the problem of traffic jams, which are common in almost every urban area worldwide, and the importance of managing traffic using real-time information. It focuses on traffic control systems based on IoT technology, describing their hardware and software systems and analyzing their operation in an urban context. The study highlights both the advantages and disadvantages of IoT-based traffic control systems, emphasizing that while they have their benefits, they also have certain limitations that must be considered in their design and implementation.

Syed et al. in [39] provides a comprehensive overview of the application of IoT technologies in smart cities, which enable the integration of various devices and technologies, eliminating the need for human intervention. It describes the basic components of the landscape of IoT-based cities and the technologies enabling the operation of these systems, including architectures, network technologies and artificial intelligence algorithms used in smart city systems. The paper also reviews the most commonly used practices and applications in various smart city domains and discusses the challenges of implementing IoT systems in cities while offering countermeasures.

Shah et al. in [40] review existing IoT-based solutions in waste management systems in smart cities, highlighting their role in ensuring sustainable development. It analyzes 16 research articles from the last 5 years to present the state of knowledge about IoT solutions in monitoring waste levels, technologies used and possible solutions. The results indicate that while existing solutions are similar regarding their integration platforms with IoT technologies, they differ in the sensors and communication technologies used, with many previous studies using Arduino Uno. The article supports further research into developing new technologies and improving existing systems.

Laha et al. in [41] present an overview of the impact of IoT technologies on environmental monitoring, covering air quality, water pollution and waste management. Provides an analysis of the development of environmental monitoring systems that have evolved from basic remote monitoring systems to advanced environmental monitoring systems using IoT technology and advanced sensor modules. The study focuses on assessing numerous studies on monitoring air quality, water, waste and general environmental pollution and their impact on the environment, classifying studies by objectives, methods and results, and analyzing the use of sensor technologies, the IoT, and machine learning.

Arjun et al. in [42] present research on using IoT technologies to modernize street lighting systems to reduce energy waste and improve urban lighting management efficiency. Instead of traditional, manual systems that lead to significant energy waste, the article describes how the IoT can automate street lighting, which is crucial to solving the energy crisis. The work discusses various sensors and components used in intelligent lighting systems, which, although often simple, are effective in creating modern, intelligent lighting management systems. The compilation of these articles provides a comprehensive overview of the various applications of the IoT in monitoring and control, showing their importance in various areas of life and industry.

3. Monitoring and Control Systems Based on IoT

In today’s dynamic technological environment, the IoT sets new standards for managing and controlling various systems. IoT-based monitoring and control systems are key in smart buildings, industry, and the health sector. This chapter looks at the latest trends and solutions in this field, considering the benefits and challenges of implementing these systems. It also examines the development prospects and what new technologies may shape the future of monitoring and control systems.

3.1. IoT-Based Predictive Maintenance Systems

Nangia et al. in [43] discusses a system for predicting damage in the manufacturing sector designed to minimize downtime and early detection of damage to production machines. This system integrates various IoT-based sensors and uses artificial intelligence to analyze and make decisions about potential failure points. The system consists of a network of sensors placed at strategic points that constantly monitor various operating parameters of machines on the production line, such as temperature, humidity, pressure, current, vibration, air quality, and gas. Additionally, specialized sensors, such as ultrasonic and photoionization, were used. These sensors are connected to a central management system that collects data from many sources and transmits it to the cloud for further processing and analysis. The data cloud uses advanced machine learning algorithms such as the PdM algorithm to identify patterns, forecast trends and generate reports for end users. The described IoT-based environmental monitoring system is an innovative solution that allows for effective monitoring and early detection of machine failures. Its versatile applications and advantages make it a valuable contribution to monitoring and predicting failures using modern technologies.

Elkateb et al. in [44] present an innovative system based on IoT technology, specifically designed for predictive maintenance of circular knitting machines. Machines of this type are crucial for the textile industry, and their unplanned downtimes can generate significant costs and disrupt the production process. The IoT-based system enables real-time monitoring of machines, identification of potential faults, and effective maintenance planning, contributing to increased operational efficiency and cost reduction associated with machine maintenance. The system consists of an advanced printed circuit board (PCB) with an ESP32 microcontroller and various sensors, including speed and machine stop detection. These sensors allow the system to monitor various machine stops such as lycra stop, gate stop, idle stop (caused by human interaction), feeder stop, needle stop, and completed roll. Data collected by the system are stored in a MongoDB database, enabling further analysis and utilization in predictive machine maintenance. The system has been deployed on two different PAILONG circular knitting machines operating at an ambient temperature of 26 degrees Celsius. By utilizing data collected from the sensors, the system provides comprehensive real-time monitoring of the machines, enabling quick detection of potential faults and efficient maintenance planning. The system’s main advantage is its ability to provide real-time monitoring of machines and prompt response to any abnormalities in operation. By identifying the cause of machine stoppages, operators can take immediate corrective actions, minimizing downtime and preventing potential breakdowns.

Additionally, IoT technology allows for collecting and analysing large amounts of data, creating increasingly accurate predictive models that can anticipate future machine faults with greater precision. The described IoT system for the predictive maintenance of circular knitting machines represents a significant step forward in the textile industry’s industrial maintenance field. Its implementation can significantly increase operational efficiency, reduce machine maintenance costs, and ensure smooth production processes by minimizing unplanned downtimes. It is an excellent example of leveraging modern technologies to improve performance and competitiveness in the industrial sector.

Mourtzis et al. in [45] noticed that the contemporary digitization of manufacturing processes and shifting market demand towards products and services with lower costs have led to the emergence of Product-Service Systems (PSS). The article emphasizes the importance of maintenance, repair, and training within PSS, combined with Augmented Reality (AR). Analyzing large datasets generated by sensors enables quick decision-making. In recent years, energy efficiency issues have become a production priority. Energy consumption significantly impacts costs and production quality. The “cold chain” encompasses equipment and processes that ensure proper conditions for perishable goods from production to consumption. Refrigeration and Cold Storage Systems (RCSS) play a crucial role in preserving the freshness of goods but consume over 50% of supermarket energy. Therefore, monitoring data is essential for optimizing RCSS operation and preventing breakdowns. Existing literature presents various approaches to detecting anomalies in cooling systems. Approaches based on energy analysis, machine learning methods, and fault diagnosis systems have been mentioned.

There are also tools for monitoring energy consumption and detecting refrigerant leaks. Scientific work has proposed monitoring and predictive maintenance systems that leverage IoT technologies and artificial intelligence. The proposed system architecture is based on sensor networks and cloud computing. Components include sensor nodes, a network application, and a user interface. Communication protocols such as HTTP, WebSocket, and TCP are utilized. Deployment involves integrating databases, servers, and software to ensure data flow between them. Sensor nodes have various sensors and communication modules such as Particle Device OS and XBee Wi-Fi. The user interface enables data visualization and the receiving of alerts about failures. The software is developed using NodeJS, MongoDB, and WebSocket technologies. Implementation includes deploying a sensor network management system that handles communication between sensor nodes and the network application. A prototype device for data acquisition has been developed using microcontrollers and communication modules. This device integrates various sensors, enabling monitoring conditions in refrigeration chambers.

3.2. Monitoring and Control Systems for Smart Agriculture Based on IoT

The development of technology in recent decades has revolutionized many areas of life, including agriculture. Modern agriculture increasingly uses advanced technological solutions that enable production optimization, increased efficiency and cost reduction. One key element of this transformation is monitoring and control systems based on IoT technology. The IoT in agriculture, or precision agriculture, involves using various sensors, devices and analytical systems to collect and analyze data in real time. Introducing IoT systems to agriculture brings many benefits, from monitoring soil and weather conditions through irrigation management to remotely controlling agricultural machines. This makes it possible to increase yields and manage natural resources more sustainably, which is particularly important in the context of climate change and growing requirements for environmental protection.

Rajesh et al. in [46] discuss the transition from manual methods of parameter verification to automated systems using temperature and humidity sensors. They highlighted the development of algorithms programmed into microcontroller-based gateways for effective crop monitoring. Integrating photovoltaic panels for power and a cellular internet interface provides additional functionality to the system. Additionally, advances in wireless networks enable the creation of innovative farming solutions, including remotely controlled GPS-based robots for various tasks such as weeding, spraying, and measuring humidity.

The basic components of the intelligent monitoring system are an Arduino Uno microcontroller board, a GSM modem for communication, a soil moisture sensor, a humidity sensor, a PIR sensor, an LCD, a speaker and ThingSpeak for IoT analysis. These components work together to collect data from the field continuously, compare it to predefined thresholds, and initiate appropriate actions such as turning on fans to regulate temperature or sending alerts to the farmer via SMS or IoT platforms such as ThingSpeak. The system works by continuously collecting data from sensors in the field, including temperature, soil moisture and human presence. When values exceeding predefined thresholds are detected, appropriate actions are initiated, such as turning on fans to regulate the temperature or sending alerts to the farmer via SMS or IoT platforms such as ThingSpeak. The cyclical process ensures real-time monitoring and timely interventions, ultimately leading to the optimization of agricultural practices. A visual representation of the system’s work process is presented in a flowchart, illustrating the sequential steps involved in data collection, analysis and action initiation.

Implementing smart agricultural monitoring systems is proving to be very beneficial for farmers. These systems enable them to receive relevant information and data in real time that can be used to make quick decisions. Farmers can receive alerts and monitor field conditions remotely using a GSM modem and Wi-Fi modules, enabling quick interventions and ensuring optimal crop health.

Suma et al. in [47] presents a comprehensive agricultural monitoring system based on IoT technology that uses various sensors such as temperature, humidity, soil moisture and PIR sensors. The data collected by these sensors is transmitted to the microcontroller via the RS232 interface. The control section compares the collected data to the threshold values. If the data exceed the threshold, an audible alarm sounds, and the LED flashes. An alarm is sent as a message to the farmer, after which the power automatically turns off. In manual mode, the user can turn the microcontroller on and off using a button in the Android mobile application, which is carried out using the GSM module. In automatic mode, the microcontroller is turned on and off automatically if the value exceeds the threshold point, and the user automatically receives an alert via SMS. Apart from this, parameters such as temperature, humidity, soil moisture, and PIR sensors show the threshold value. The water level sensor indicates the water level in the tank or water source. The system uses a PIC16F877A microcontroller, a GSM module and various sensors such as a soil moisture sensor, an LM35 temperature sensor and a PIR sensor. The RS232 interface enables communication with a GSM modem to send and receive SMS and telephone calls. The soil moisture sensor uses both analog and digital output, and the LM35 temperature sensor offers a linear output with a range of −55 to +150 degrees Celsius. The PIR sensor detects the movement of people, animals or other objects using infrared radiation. Proteus 8 software was used to simulate the electronic system. The conclusions from the experiment show that the system is a complete solution to field operations and irrigation problems, which can help to improve crop yields and overall agricultural production. In the future, the system can be developed for larger land areas and integrated with soil quality control and plant growth in each soil.

In [48], Mini et al. present a comprehensive IoT system to support agriculture by monitoring environmental conditions and remotely controlling robotic vehicles. The proposed system uses two microcomputers, Arduino Nano and ESP32, which cooperate to collect sensor data and manage vehicle traffic. The Arduino Nano acts as the control unit, managing the vehicle’s movement, while the ESP32 acts as the sensor unit, collecting data on temperature, humidity, and soil moisture. These data are then transmitted to the ThingSpeak IoT platform using the built-in ESP32 Wi-Fi module, allowing it to be stored and analyzed in real time. The system also includes DC motors and a motor controller, DHT11 and soil moisture sensors, lithium-ion batteries, a Buck converter that stabilizes the voltage, an HC05 Bluetooth module enabling communication with a mobile application, a buzzer signaling low soil moisture levels, and an OLED display presenting environmental data. Programming is performed using the Arduino IDE, which allows us to write, test and debug code easily. The system collects data via ESP32 and sends it to the cloud, while Arduino Nano controls the vehicle’s movement based on commands from the mobile application. When the soil moisture level drops below the threshold, a buzzer signals watering needs. The mobile application allows us to monitor data and remotely control the vehicle in real time. The collected data are analyzed on the ThingSpeak IoT platform, which allows farmers to manage resources effectively. The proposed system offers innovative solutions for agriculture, especially in rural India, where access to advanced technologies is limited, yields are increasing, resource wastage is reduced, and environmental sustainability is improved.

In recent years, the energy sector has been undergoing a significant transformation, driven mainly by the development of modern information and communication technologies. One key element of this evolution is intelligent energy grids, which integrate advanced monitoring and control systems that enable more efficient energy production, distribution and consumption management. The IoT plays a central role in these systems, which allows data to be collected, transmitted, and analyzed in real time from various points of the energy network. Smart energy grids equipped with IoT solutions offer numerous benefits, including improving the reliability of energy supply, optimizing energy consumption and increasing operational efficiency. Thanks to sensors, smart meters and advanced analytical algorithms, it is possible to quickly detect and respond to failures, predict energy consumption patterns, and integrate renewable energy sources more sustainably and efficiently.

Bagdadee et al. in [49] noticed that in the face of complex challenges related to the effective management of electricity, there is a need to develop effective strategies to optimize the location and performance of energy-generating units in distributed systems. This paper presents a multi-objective analysis approach, focusing on power quality and voltage stability issues, to determine the optimal parameters for the location and operation of distributed units. This approach’s basis is power quality and voltage stability indicators, effectively combining the effects of increasing real and apparent reactive power. The systematic characterization of these indicators allows for constructing objective functions that consider both power quality and voltage stability issues. The leading equipment used in the proposed system are Arduino-based systems, remote sensors, ultrasonic sensors, and GSM modules. This system allows us to measure power and send the collected data to local offices. Arduino chips form the system’s core, providing an interface for receiving and processing sensor data and communicating with the central office via GSM modules.

When analyzing power quality, DMR (DMR meters) meters measure parameters such as power consumption, cable defects, and voltage anomalies, providing a detailed analysis of power quality in a low-voltage system. GSM modules transmit data from DMR meters to the control panel, ensuring a quick response to possible power quality problems. To effectively control power flow and maintain voltage stability, the proposed system uses dynamic power control techniques to ensure smooth operation of the network under various load conditions.

Additionally, this system can monitor and respond to changes in the network in real time, allowing for quick identification and resolution of potential power quality problems. The simulation analysis’s conclusions confirm the proposed system’s effectiveness in managing electricity in smart energy grids. Thanks to advanced IoT technologies and multi-objective analysis, this system enables optimal location and efficiency of energy-generating units in distributed systems. This translates into increased reliability and efficiency of the entire energy system.

Sulthana et al. in [50] present the design and implementation of an intelligent energy consumption monitoring system that enables automatic reading of the electricity meter and management of electrical devices at home using a dedicated mobile application. The system is based on several key components such as Arduino, a Wi-Fi module, an energy meter, a relay and a transformer. The energy meter used in the system is a clamp-on meter that measures the current voltage, current and power in units of kWh. The Arduino microcontroller reads these parameters and transmits them to the cloud, which allows the user to access current data via the mobile application. Data communication takes place via the Wi-Fi module, which is configured with Arduino. This module allows us to transfer data from the energy meter to the cloud and control electrical devices in our home using a mobile application. The relay controls a home circuit using Arduino, allowing us to turn the circuit on and off using a dedicated mobile app. The transformer converts the mains voltage into a low voltage suitable for the Arduino microcontroller. The system uses the IoT, enabling communication between network devices and remote controls. Expected system results include the real-time monitoring of energy consumption and automatic notification to the user when energy consumption reaches a certain level. The system also allows us to remotely manage electrical devices at home via a dedicated mobile application. The conclusions suggest that an intelligent energy monitoring system provides user convenience by remotely monitoring and managing home energy consumption while reducing the need to manually read energy meters, leading to time and labour savings.

In [51], the authors discuss advanced strategies for monitoring and managing electricity consumption, introducing modern approaches based on IoT technology within intelligent energy grids. Traditional energy transmission systems relied on one-way communication, which hindered the user’s ability to generate energy. The solution to these challenges is microgrids and intelligent energy grids that use the latest technologies, such as smart energy meters and the IoT, to enable more efficient, flexible and transparent monitoring and control of energy transactions. Intelligent grids include hybrid power generation, integrating renewable sources such as solar, wind and fuel cells, and using advanced algorithms such as Perturb and Observe for maximum power point tracking (MPPT). The article details the architecture of a power monitoring and control system for solar power generation and how various components, such as Arduino and Raspberry Pi microcontrollers, communicate. Experiments conducted as part of the research confirm the effectiveness of the proposed solutions in monitoring and controlling energy consumption in intelligent energy networks, which contributes to increasing energy efficiency and sustainability.

3.3. IoT-Based Monitoring and Control Systems for Healthcare

Health care is one of the most dynamically developing fields in which technology plays a crucial role in improving the quality of medical care. One of the most promising trends is the integration of IoT technologies into monitoring and control systems, which transforms how patients are diagnosed, treated, and monitored. The IoT in healthcare includes a wide range of devices and applications that enable the collection of medical data in real time, their analysis, and the transfer of information to healthcare systems, allowing for the more precise and effective management of patient’s health. The use of the IoT in healthcare brings many benefits, such as remote monitoring of patients, which is especially important for people who are chronically ill, elderly, or living in remote locations. Smart devices such as wearable sensors, smart inhalers, and advanced monitoring systems in hospitals allow for continuous tracking of patients’ vital signs, detection of early signs of health deterioration, and immediate medical intervention.

Vasalan et al. in [52] detail the design and implementation of an intelligent patient health tracking system that uses sensors to monitor key health parameters such as body temperature and heart rate and environmental conditions such as humidity and room temperature. These sensors are connected to an Arduino microcontroller that processes the data, displays it on an LCD screen, and transmits it to the cloud via Zigbee wireless technology.

Communication between the sensors and the central server takes place using the Zigbee protocol, which is ideal for applications in sensor networks due to its low energy consumption and the ability to create large mesh networks. Data are transmitted from the local server via WLAN to the medical central server, where it is analyzed and stored. If the patient’s previous medical data are missing, the system creates a new identification and starts monitoring. Experimental results, including patient health simulations with various combinations of body temperature and heart rate, confirm that the system effectively diagnoses health conditions such as fever, hypothermia, or the need for immediate medical consultation. The conclusions indicate that the use of IoT technology significantly increases the availability of healthcare, reduces the costs of medical visits and hospitalizations, and enables quick and effective responses to changes in patient’s health status, which may be particularly important in crises such as epidemics.

In [53], the authors focus on the role of the IoT in modernizing healthcare systems, emphasizing the importance of remote patient monitoring to improve the availability and quality of medical services. In India, where many people suffer daily from a lack of adequate and timely medical care, developing reliable patient monitoring systems that can be used in hospitals and everyday life becomes crucial. The system described in the article uses the Arduino microcontroller due to its simplicity, ecological characteristics, and low costs. Arduino is the heart of the system, integrating various sensors such as the LM35 temperature sensor, heart rate sensor, pulse oximeter, blood pressure sensor, and ECG sensor. These sensors measure parameters such as body temperature, heart rate, oxygen saturation, and blood pressure, transmitting these data to the microcontroller. Communication in the system occurs via an Ethernet module, which enables an interface with the Arduino microcontroller and connection to the network. This module, which has an IP and MAC address, stores programs and transmits data to the network, allowing authorized users to access information remotely. Data from sensors are sent to the cloud via a wireless network (WSN), which allows them to be accessed from anywhere in the world.

The article also discusses the software for processing data, including scripting languages such as PHP, JSON, and the MySQL database management system. Patient data are stored on a server and published to enable medical staff to monitor it remotely. The experiments confirmed the system’s effectiveness in monitoring and diagnosing patients’ health conditions. Research conclusions suggest that the IoT in healthcare systems can significantly improve the availability and quality of medical services, especially in rural and hard-to-reach regions. By monitoring patients remotely, doctors can keep up to date with the health of their patients, which can lead to faster responses to changes and better health care.

Bhardwaj et al. in [54] present a comprehensive health monitoring system designed to help diagnose and monitor patients with COVID-19. The system consists of various hardware components, including a microcontroller with a built-in ADC converter, a blood pressure sensor, a non-contact temperature sensor, and an oximeter. The sensors are connected to a Raspberry Pi microcontroller responsible for collecting and transmitting data to the cloud for storage and further analysis. This allows it to automate various systems and cooperate with sensors and external devices. Additionally, the system is scalable, which means it can monitor multiple patients simultaneously, a significant advantage in a medical setting. The system operation process can be divided into three main stages: data collection, data processing, and storage and display of patient parameters. In the first phase, data from the sensors are collected and transferred to the Raspberry Pi microcontroller, where they are processed. The processed data are recorded in the next stage using the I2C interface or other appropriate communication protocols. Finally, the data are stored in the cloud and displayed on a monitor, allowing doctors to quickly and easily monitor patients’ condition. While testing the system on various patients, the effectiveness of monitoring health parameters such as heart rate, body temperature, blood pressure, and oxygen level was examined. Comparison test results with commercial sensors showed promising results, with minimal relative errors. The system was also tested for scalability, confirming its ability to monitor multiple patients simultaneously. The research conclusions indicate that the developed health monitoring system based on the IoT can effectively aid in diagnosing and monitoring patients with COVID-19.

3.4. Monitoring and Control Systems for Environmental Protection Based on IoT

In the face of increasing challenges related to climate change, environmental pollution, and the need for sustainable management of natural resources, technology plays an increasingly important role in protecting our planet. One of the most significant achievements in this field is using IoT technology in monitoring and control systems. The IoT enables the collection, analysis, and transmission of environmental data in real time, which allows for better understanding and management of processes occurring in ecosystems. Implementing IoT systems in environmental protection brings numerous benefits such as monitoring air and water quality, waste management, controlling greenhouse gas emissions, and protecting biodiversity. Thanks to a network of sensors, drones, satellites, and advanced analytical systems, it is possible to quickly detect threats such as leaks of hazardous substances, forest fires, or changes in wild animal habitats. This, in turn, allows us to take immediate preventive and protective actions, minimizing the negative impact on the environment.

In [55], the authors describe an advanced environmental monitoring system using mobile robots and IoT technology. Mobile robots have many applications, including monitoring and security, transportation of goods, domestic purposes, and many others. In the work, scientists present a network based on mobile robots designed for remote monitoring and ensuring security via the Internet using the Web IoT platform. Mobile robots remotely controlled via the Internet have been used in various fields such as the manufacturing industry, storage condition assessment, maintenance of nuclear power plants, space exploration, etc. The project used various sensors to monitor the environment, including gas, temperature, and humidity sensors. Data from these sensors are collected by Raspberry Pi and sent to the cloud, where it can be analyzed and used by users using various devices such as notebook computers or smartphones. The system uses Raspberry Pi to communicate with various sensors and control mobile robots. The robots are equipped with Arduino Mega microcontrollers, GPS, compasses, DC motors, and other components necessary for navigation and motion control. All collected data are sent to the IoT platform, which can be analyzed in real time and displayed to users in graphical form. The system has gas, temperature, and humidity sensors for accurate environmental monitoring. Data from these sensors are collected and sent to the cloud, which can be analyzed and displayed to users in a graphical form.

Additionally, the system allows us to control the movement of mobile robots using a mobile application, which allows users to interact with them in real time. The research conclusions indicate that the developed environmental monitoring system using mobile robots and IoT technology can be an effective tool for monitoring and ensuring safety in various fields, including agriculture, air quality monitoring, and weather forecasting. Additionally, this system is scalable and can be adapted to various conditions and user requirements.

Rani et al. in [56] describe an advanced weather monitoring system based on IoT technology, which enables easy access to real-time data on a large scale. This system uses various sensors to monitor many weather parameters such as temperature, humidity, wind speed, light intensity, UV radiation, carbon monoxide levels, soil moisture, rainwater, and precipitation. It includes, among others, DHT11 sensors for measuring temperature and humidity, an anemometer for measuring wind speed, LDR for measuring light intensity, GY8511 for measuring UV radiation, MQ7 for measuring carbon monoxide levels, a hygrometer for measuring soil moisture and rain sensors for detecting precipitation atmospheric. Many features and benefits characterize the system. Its compact design allows for easy rooftop installation and portability to remote locations. Low energy demand enables power supply from solar panels, which reduces costs and enables long-term monitoring in areas where access to power is limited. In addition, the costs of the sensors are lower than in the case of traditional weather monitoring systems, which makes the project more profitable.

Data from the sensors are sent to the website, where they are presented in graphic statistics, enabling access from anywhere in the world and their future use. With fewer moving parts, the system requires less maintenance, which reduces maintenance costs. Additionally, the mobile application sends notifications about sudden weather changes, acting as an effective warning system against unfavorable conditions. The system uses a Raspberry Pi API for more advanced weather forecasts, which analyzes sensor data and predicts accurate results. The system consists of an Arduino Uno microcontroller as the central data processing module, and the sensor data are processed and sent to the database on the website using Node MCU and Ubi dots.

The authors of [57] discuss the growing problem of air pollution, which increasingly affects society due to the rapid development of industrialization and the number of vehicles. Harmful substances in the air, such as terrestrial ozone, nitrogen dioxide, and sulfur dioxide, threaten nature and human health. Chemical pollutants, including suspended particles, carbon monoxide, nitrogen oxides, sulfur oxides, lead aerosols, and volatile organic compounds, contribute to increased disease rates. Advanced research in sensor networks and wireless communication technology has produced several applications of wireless sensor networks in environmental monitoring and pollution control. The paper discusses air pollution monitoring and quality control using sensor nodes in a wireless sensor network. This project aims to create a real-time air pollution monitoring system using IoT technology, enabling the recording of atmospheric pollutant concentrations and establishing action plans for detecting high pollution levels. The system also aims to monitor air quality levels in selected cities with heavy road traffic. Existing monitoring systems are expensive and often use a single sensor, making comprehensive monitoring of air pollutants impossible. In the proposed system, we use many sensors that can detect various types of gases and pollutants present in the air. Data from these sensors are transmitted to the Blynk 2.0 cloud via Wi-Fi connectivity, enabling real-time air quality monitoring via the Blynk smartphone app and the Blynk dashboard in graphs. This design has a low cost and compact size, which makes it portable and easy to maintain. It also has great development potential, enabling additional sensors and integration with smart city initiatives. The project used the ESP32 microcontroller (Node MCU), which reads data from all sensors and then transmits them to the Blynk 2.0 cloud via Wi-Fi. The system also uses the Blynk 2.0 cloud to present data in real time on a mobile application and a web panel. This way, users can easily monitor air quality and receive notifications when pollutants are detected.

3.5. Monitoring and Control Systems for Smart Cities Based on IoT

With the dynamic development of urbanization and the growing urban population, cities worldwide face numerous challenges related to infrastructure, transport, resource management, and the quality of life of their inhabitants. Advanced technologies, including the IoT, are increasingly used to meet these challenges and make cities more effective, sustainable, and friendly to residents. Smart cities use the IoT to create integrated monitoring and control systems that enable the collection and analysis of data in real time, improving the management of urban infrastructure and services. IoT systems in smart cities are widely used, from road traffic monitoring and public transport management through intelligent street lighting to waste management and air quality monitoring. Thanks to sensors, communication networks, and advanced analytical algorithms, cities can respond more effectively to the needs of residents, optimize energy and resource consumption, and improve the safety and comfort of life.

Sudha et al. in [58] present an innovative approach to street lighting control and monitoring based on IoT technology, representing a breakthrough in urban lighting infrastructure, offering intelligent, more tailored solutions that consider the dynamic needs of modern cities. Using technologies such as NodeMCU microcontrollers, relay modules, light-dependent resistors (LDRs), and motion and environmental sensors, these systems enable dynamic lighting level adjustment depending on traffic, pedestrian activity, and light conditions.

Integrating remote monitoring and management enables city governments to proactively identify problems, optimize performance, and reduce operational costs. Through cause-and-effect analysis, complex control algorithms consider traffic, pedestrian activity, time of day, and weather conditions to optimize lighting levels. It is worth noting that the NodeMCU ESP8266 microcontrollers used constitute the central control units, enabling communication between relays, LDR, and LED sensors. LDRs, strategically placed in urban areas, collect data on light intensity, and relay modules control street lighting.

The system’s operation scheme involves using LDR sensors to collect light-intensity data, which is then processed by the NodeMCU ESP8266 microcontroller. Based on these data, the system makes decisions regarding street lighting control, which allows for optimizing energy consumption and minimizing operating costs. The above-mentioned elements and data integration from many sensors and control algorithms constitute a comprehensive system that ensures effective, energy-saving, and intelligent street lighting, which positively affects residents’ quality of life and the urban environment.

In [59], the authors present the importance of the problem of environmental pollution by waste and the need to monitor and manage it to protect the environment. Accumulating garbage around streets can be a breeding ground for rats and fleas that carry harmful diseases, leading to epidemics and deaths. Therefore, it is necessary to introduce a waste monitoring system to reduce pollution. The article discusses various IoT-based approaches to waste monitoring, such as intelligent garbage bins using infrared and load sensors, GSM-based alarm systems, and RFID and Zigbee-based systems. In addition, an analysis of municipal waste management in various regions of the world was presented, and the benefits of using intelligent waste monitoring solutions were discussed. As part of the experiments in the article, a waste monitoring system based on the Thingspeak platform was proposed, using ultrasonic sensors and load sensors that collect data on the level and weight of waste in the bin. These data are transmitted in real time to the Thingspeak platform, where it is updated and made publicly available, allowing users to monitor the status of their bin online. Experimental results show that the proposed system effectively monitors the level and weight of waste in the bin, which allows for effective waste collection and disposal management. Additionally, using the Twitter platform to share updates on the status of the bin helps to increase public awareness of waste management and environmental protection. The article’s conclusions indicate that intelligent waste monitoring systems can improve city cleanliness, environmental hygiene, and intelligent waste management, which is an important step towards sustainable development and environmental protection.

Priya et al. in [60] noticed that the IoT plays a crucial role in intelligent parking systems. Sensors installed in parking lots collect data on the availability of parking spaces, which are then processed and analyzed to manage parking applications effectively. Traditional parking management systems often need help accurately detect available spaces, especially in large, free parking lots. To overcome them, the paper proposes using infrared sensors to precisely detect parking spaces, eliminating problems related to accuracy, lighting conditions, and weather.

The system architecture includes several phases, including the development of an Android application for parking reservations, identification of vacant spaces using infrared sensors, user authentication using RFID tags, classification of parking spaces based on vehicle size, and navigation to assigned spaces using GPS. In particular, the system is based on Arduino Uno microcontrollers, which are microcontrollers based on the ATmega328P system. They have 14 digital I/O pins, six analog pins, a USB interface, and many other features such as Arduino IDE software programs and interfaces with sensors, Wi-Fi, and RFID modules. Additionally, the system provides visualization tools for parking center owners to monitor reservation details, space availability, and billing information. Implementation details highlight using Arduino microcontrollers, RFID readers, and Wi-Fi modules to enable communication between sensors, mobile applications, and backend systems. The paper also includes experimental results that demonstrate the effectiveness of the proposed system in optimizing parking space utilization and improving user experience.

In summary, the IoT-based smart parking system presented in this paper offers a promising solution for efficient parking management in urban areas. Although the prototype focuses on single-story parking lots, the model can be scaled to multi-story parking facilities, thus contributing to the overall development of innovative city initiatives.

3.6. IoT-Based Monitoring and Control Systems for Transport and Logistics

In the era of globalization and dynamic technological development, the transport and logistics industry faces increasing challenges related to the efficiency, safety, and sustainable management of supply chains. Enterprises increasingly turn to advanced technologies, including the IoT, to meet these challenges. The IoT in transport and logistics enables the collection, analysis, and exchange of data in real time, which allows for more precise monitoring and control of logistics and transport processes. Implementing IoT systems in this industry brings numerous benefits such as route optimization, monitoring transport conditions, vehicle fleet management and real-time shipment tracking. Thanks to sensors, GPS devices, RFID technology and advanced analytical systems, enterprises can increase operational efficiency, reduce costs and improve service quality. In addition, the IoT helps increase transport safety by monitoring the technical condition of vehicles and road conditions.

Salih et al. in [61] proposed an intelligent public communication system based on advanced technology based on a mobile application and the ESP32 microcontroller with a Wi-Fi and GPS module. This microcontroller is installed in each bus, which allows for the real-time monitoring of the vehicle’s location and speed. These data are then sent to a cloud server, which is analyzed and made available to users via a mobile application. Within this application, passengers can track the location of buses on Google Maps, find out the estimated arrival time, and calculate the distance to the nearest vehicle. The system operates continuously and automatically: the GPS module in each bus constantly communicates with satellites to obtain current geographical coordinates and speed. These data are then sent via Wi-Fi to the server, processed, and made available in real time to mobile application users. Thanks to this, passengers can quickly and easily obtain the necessary information about the location and arrival time of buses, which allows them to plan their trip better and minimize waiting time at the bus stop. It is worth noting that the proposed system is characterized by ease of use and low costs, making it an attractive solution for public transport users.

Additionally, tests on the streets of Mosul confirmed its effectiveness, which showed high accuracy in determining the location and arrival time of buses. The system will be further developed by adding additional functions to the mobile application, such as passenger counting using sensors and introducing an electronic ticketing system using RFID tags. Thanks to continuous development and improvement, the proposed system has the potential to become an indispensable tool for public transport users, providing them with a fast and comfortable journey.

The authors of [62] propose a bus tracking system using advanced technologies such as RFID, GPS, and GSM to increase the safety of students’ travel between home and college. The problem of long waits at bus stops and the increasing number of crimes against students were mentioned, which makes parents concerned. Therefore, the authors proposed a system to monitor students’ travel and notify parents about their safety. The system is based on RFID technology, which is used to identify students through unique RFID cards placed in their backpacks. When a student enters, leaves the bus, or exceeds the speed limit, the system automatically sends notifications to parents via SMS and mobile application.

Additionally, the GPS module tracks the bus’s location in real time, and the GSM module is used to send notifications. The system consists of three central units: the bus unit, the parent unit, and the college unit. The bus unit has an RFID reader, a GPS module, a GSM module, and a PIC16F877A microcontroller. When a student enters or leaves the bus, the RFID reader records these events, and the GSM module sends notifications to parents. In addition, the system can also detect fires thanks to the use of a fire sensor. The parent unit consists of a mobile application that allows parents to track their students’ travels and receive notifications about their safety. However, the college unit uses a web application where the administrator can manage the data related to buses, students, routes, etc. The authors emphasize that this system will increase student travel safety and facilitate the college’s bus fleet management. Additionally, they plan to develop the system further by adding parking management and bus communication functions.

4. Discussion

Each of these sectors places different requirements on IoT systems, which leads to the creation of various technological solutions. In agriculture, IoT systems monitor soil and weather conditions and manage irrigation. In health care, the IoT enables the remote monitoring of patients and the management of medical equipment. The IoT tracks shipments, optimizes routes, and manages vehicle fleets in transport and logistics. Smart cities use the IoT to manage urban infrastructure through street lighting, traffic management systems, and air quality monitoring. In environmental protection, the IoT helps monitor and manage natural resources and detect ecological threats. This chapter compares IoT-based monitoring and control systems and considers their specific applications, benefits, and challenges.

After the analysis of existing monitoring and control systems based on the IoT, a summary was made in the form of two tables:

Table 1. Platforms used in the systems.

Platforms	Systems	Website	Accessed
Arduino	[46,49,50,51,53,55,60]	www.arduino.cc	1 July 2024
ESP32	[44,48,57,61]	www.espressif.com	2 July 2024
ESP8266	[58]	www.espressif.com	2 July 2024
MCU MT3620	[63]	www.mediatek.com/products/iot-genio/mt3620	5 July 2024
PIC16F877A	[47,62]	www.microchip.com	4 July 2024
Raspberry Pi	[51,54,55,56]	www.raspberrypi.com	6 July 2024

lists the platforms used in the systems, and

Table 2. Protocols used for data transmission.

Protocol	Systems
Bluetooth	[43,48]
MQTT	[44]
HTTP	[45]
GSM	[46,47,49,59,62]
Zigbee	[52,60]
Ethernet	[53]
RFID	[59,60,61,62]

lists the protocols used for data transmission. We distinguished seven different protocols. The authors of other solutions [43,45,48,50,51,52,53,54,55,56,57,58,60,61] only marked that they used wireless communication technology. Thus,

Table 3. Comparison of presented systems.

Paper	Used Real Prototype	Used Real Data	Practical Using	Data Management	Used AI	Discussed Security	Discussed Architecture	Used LPWAN	Discussed Energy Efficiency
[43]	−	+	+	+	+	−	+	−	−
[44]	+	+	+	+	+	−	+	−	−
[45]	+	+	+	+	−	−	+	−	−
[46]	+	+	+	+	−	−	+	−	−
[47]	+	+	+	+	−	−	+	−	−
[48]	+	+	+	+	−	−	+	−	−
[49]	+	+	+	−	−	−	+	−	−
[50]	+	+	+	−	−	−	+	−	−
[51]	+	+	+	+	−	−	+	−	−
[52]	+	+	+	+	−	−	+	−	−
[53]	+	+	+	+	−	−	+	−	−
[54]	+	+	+	+	+	−	+	−	−
[55]	+	+	+	+	−	−	+	−	−
[56]	+	+	+	+	+	−	+	−	−
[57]	+	+	+	−	−	−	+	−	−
[58]	+	+	+	+	−	−	+	−	−
[59]	+	+	+	+	−	−	+	−	−
[60]	+	+	+	+	+	−	+	−	−
[63]	+	+	+	+	−	−	+	−	−
[61]	+	+	+	+	−	−	+	−	−
[62]	+	+	+	+	−	−	+	−	−

compares the presented system in the scope of chosen parameters.

One can see a wealth of choices when considering the microcontrollers used in the examined examples of IoT-based monitoring and control systems. Among them, the three most popular options are Arduino in various variants, ESP32, and Raspberry Pi. Each solution has unique features and capabilities that allow it to adapt to various design needs. Known for its reliability and versatility, Arduino [64] offers a wide range of boards and modules that enable rapid prototyping [65] and easy scaling of projects [66]. ESP32 [67], in turn, is distinguished by advanced communication functions [68], which makes it an excellent choice for projects requiring connection to Wi-Fi and Bluetooth networks [69]. However, Raspberry Pi [70], thanks to its computing power and expansion possibilities [71], is an ideal candidate for more advanced applications where support for the operating system and applications [72] of greater complexity is needed. Thanks to the diversity of these platforms, designers and developers have a wide range of tools to implement their ideas related to the IoT.

When analyzing the protocols or solutions used for data transmission in IoT systems, it is worth noting that one of the most frequently used is undoubtedly Wi-Fi [73] due to its universality, ease of implementation, and high data throughput. Wi-Fi enables fast and stable wireless connections [74], which makes it an ideal choice for projects that require real-time data transmission, such as environmental monitoring or controlling devices from anywhere via the Internet. Apart from Wi-Fi, another frequently used protocol is GSM, which allows communication via a cellular network. This is especially useful in cases where there is no access to a Wi-Fi network or when you need to monitor devices in areas outside the range of your wireless network. Additionally, GSM [75] is used in security systems, vehicle monitoring, and industrial automation, where reliability and wide range [76] are crucial. Both protocols are popular not only because of their technical capabilities but also because of the support from microcontroller manufacturers. There is extensive documentation and a wide selection of modules supporting both Wi-Fi and GSM standards, which significantly facilitates the integration of these solutions into IoT projects. Thanks to this, engineers and creators can quickly and effectively implement communication functions in their projects without spending too much time developing communication solutions.

Low Power Wide Area Network (LPWAN) technology is key in ensuring effective and reliable communication between devices distributed over large areas on the IoT era. LPWAN is a group of network technologies designed for long-distance communication with low power consumption, making it an ideal solution for many IoT applications, including monitoring systems.

The analyzed monitoring and control systems based on IoT technology did not use the LoRa communication protocol. LoRa offers vast opportunities for development and research, thanks to its unique properties that enable devices to communicate in places without GSM network coverage. This is particularly important in IoT applications operating in hard-to-reach areas, such as rural areas, forests, or mountains, where traditional communication methods may fail. Implementing the LoRa protocol brings numerous benefits, including long-distance data transmission with low energy consumption, which is crucial for battery-powered devices. This allows for long-term operation of sensors and other IoT devices without frequently replacing or charging batteries, which is extremely important for keeping operating costs low. One of the main challenges related to implementing LoRa is the need to install gateways that will collect data from end devices and send them to a central server. These gateways act as communication intermediaries, enabling data transfer from distributed sensors to the cloud or local management system. Although installing such gateways may involve some costs and require appropriate infrastructure, it is an investment that can pay off thanks to the opportunities offered by independence from commercial telecommunications networks.

Moreover, LoRa is characterized by a high level of security thanks to advanced data encryption mechanisms, which is crucial in protecting information sent via IoT networks. Introducing this protocol can increase the security and reliability of monitoring and control systems, opening new perspectives for their development and implementation in various sectors such as agriculture, industry, or urban infrastructure management. To sum up, although the LoRa protocol was not used in the analyzed IoT systems, its implementation can significantly increase the functionality and range of these systems. It is, therefore, worth considering for future projects, especially where traditional communication methods fail.

Another LPWAN solution is Sigfox. It is a technology designed to transmit small amounts of data over long distances with minimal energy consumption. It operates in unlicensed frequency bands and uses Ultra Narrow Band modulation, which allows for long ranges and resistance to interference. The advantages of this solution include the operating time of devices that can operate on one battery for many years, even up to 10 years. They have a transmission range of up to 50 km in rural areas and 3–10 km in cities, and the devices used for transmission are not too expensive. The disadvantages, however, are low bandwidth of up to 12 bytes per message and transmission mainly in one direction (from the device to the cloud).

Yet another LPWAN solution is NB-IoT. Narrowband IoT technology was developed within 3GPP standards and operates in licensed frequency bands. It uses narrowband radio channels (200 kHz), which allows for high spectral efficiency and high signal penetration inside buildings. The advantages of this solution include long-range and deep penetration through building walls, the ability to support many devices in a small area, and two-way transmission. The disadvantages of this technology are the need to have a license to use the frequency and slightly higher energy consumption than in the case of LoRa or Sigfox.

LPWAN is the foundation of modern IoT monitoring systems. It offers reliable, long-distance communication with low power consumption, making it ideal for various monitoring applications. Thanks to its unique properties, LPWAN will play a key role in further developing the IoT and creating more intelligent, effective, and sustainable monitoring systems.

Also, based on our findings and thoughts, we identified seven fields of challenges and potential solutions in IoT-based monitoring and control systems. We summarized them in

Table 4. Challenges and potential solutions in IoT-based monitoring and control systems.

Challenges	Potential Solutions
Security and privacy
vulnerability to cyberattacks (malware, Distributed Denial of Service attacks), data interception; limited computing resources make it challenging to implement advanced security mechanisms	development of lightweight encryption protocols that minimize the consumption of computing power and energy; application of blockchain to secure transactions and manage the identity of IoT devices, blockchain offers security against manipulation and unauthorized access; introduction of biometric authentication increases user security
Scalability
support for dynamic device growth; diversity of generated data; network performance issues in large-scale IoT deployments	moving data processing closer to the source of their generation (edge computing) or local intermediate servers (fog computing) can relieve the central servers and network and increase the scalability of IoT systems; implementing hierarchical architectures, where data are processed at different levels, developing dynamic bandwidth management algorithms that can adjust the network bandwidth to current needs
Interoperability
use of different communication standards and protocols, which makes their integration in one network difficult; the lack of universal standards can lead to compatibility problems and make it difficult to scale IoT systems	supporting and developing open standards and protocols; creating integrated platforms for managing IoT devices that can support different protocols and standards, enabling easy integration and control
Energy management
many IoT devices operate on batteries and must be able to function for a long time without replacing them; extending the battery life and reducing the energy consumption of devices are key challenges	development of protocols that minimize energy consumption by shortening transmission time and reducing the number of transmissions; implementation of technologies that convert energy from the environment into electrical energy that powers IoT devices, extending their lifetime without the need to replace batteries; development of energy management algorithms that can dynamically adjust the energy consumption of IoT devices depending on their current needs and battery level
Precise and reliable operation
IoT systems need to be precise and reliable, especially in critical applications such as healthcare and industry	development of algorithms that can detect and automatically correct errors in real time, increasing the reliability of IoT systems in critical applications; implementation of redundant components and communication paths that can take over the functions of failed elements, ensuring system continuity; application of artificial intelligence and machine learning methods to analyze IoT data, predict failures, optimize device performance, and improve system accuracy and reliability
Throughput and latency in networks
IoT devices generate huge amounts of data that must be transmitted over the network; low bandwidth or high latency can affect the performance and reliability of systems	5G technology can significantly increase the throughput and reduce latency in IoT networks; the development of advanced compression algorithms that reduce the size of transmitted data without losing its quality allows for more efficient use of the available bandwidth; the implementation of Quality of Service mechanisms that prioritize network traffic according to its importance can ensure the reliability and smooth operation of key IoT applications
Economics and sustainability
the costs of implementing and maintaining IoT systems, especially at scale, can be high	developing subscription-based business models that allow for the gradual deployment of IoT systems without large upfront investments can make the IoT more accessible; promoting sustainable design of IoT devices that consider ease of recycling and minimize environmental impact can help address waste technology issues; supporting local manufacturing and support for IoT devices can reduce logistics costs and carbon footprints while increasing system availability and reliability

.

We also identified possible future research directions in IoT-based monitoring and control systems that can help further develop this technology. Future research should focus on creating and developing new system architectures, including hybrid solutions. Developing more flexible and modular architectures will enable easier scaling and integration of new technologies. Such architectures will allow for the dynamic adaptation of IoT systems to changing conditions and requirements. In turn, introducing hybrid architectures that combine the advantages of cloud computing, edge computing, and fog computing can increase the efficiency and flexibility of IoT systems.

The second research direction may concern autonomous IoT systems that can independently monitor, diagnose, and repair their components without human intervention. Such systems can optimize their operations with artificial intelligence and machine learning algorithms. Issues related to autonomous energy and resource management will also be exciting areas for research, as they will allow for the optimization of devices in real time and their adaptation to changing environmental conditions and application requirements.

Another direction of research in the case of monitoring and control systems concerns the use of artificial intelligence and machine learning methods. Here, research can focus on advanced analysis of data generated by IoT devices or making autonomous decisions based on real-time data analysis. Additionally, the methods mentioned above can be used to detect and counteract cyber threats in IoT systems (network monitoring, identifying anomalies, and automatically responding to threats). In addition, essential areas of research that combine the IoT and artificial intelligence are smart cities and smart agriculture. Within smart cities, IoT systems are integrated with urban infrastructure, managing traffic, energy consumption, waste management, and other resources in an automated and optimized way. Developing methods designed for this field will undoubtedly contribute to its evolution in various aspects of urban life. A similar situation occurs in the case of agriculture. These monitoring systems dedicated to agriculture (monitoring soil condition, irrigation, plant growth, or animal health) can lead to more precise and efficient agricultural production methods.

In the context of the IoT-based monitoring and control systems discussed, it is also necessary to mention the security aspects of these environments related to data, users, or the entire network to which devices are connected. As mentioned, the IoT allows for remote monitoring and control of devices over the network, which brings benefits, threats, and challenges related to security.

Many IoT devices are designed with minimal consideration for security. As a result, IoT devices are often the target of Distributed Denial of Service (DDoS) attacks, where hackers take control of many devices and use them to overload the network infrastructure, leading to disruptions in monitoring and control systems. The lack of appropriate authorization and authentication mechanisms in IoT systems can lead to unauthorized access to data or devices. Default access passwords are often used in IoT environments for a long time. In addition, many IoT devices are placed in easily accessible places, which increases the risk of physical manipulation such as disconnecting, modifying, or damaging devices. The need for more standardization and compatibility between different manufacturers can lead to security gaps. This can result in improper encryption of IoT device communications, allowing attackers to intercept sensitive personal, health, and industrial data.

Therefore, each IoT environment should be analyzed in terms of security. The first step is identifying potential threats and estimating the risk of various attack scenarios. Risk analysis helps to understand which system elements are most vulnerable and require additional protection. All data transferred between IoT devices and central systems should be properly encrypted. The SSL/TLS protocol, a widely trusted method, is commonly used to secure data transmission. Additionally, many IoT environments use special security protocols that ensure the security of authentication or the session key agreement process [77,78].

Behavior monitoring and analysis mechanisms should be implemented on the entire administrative side of the environment. Regular monitoring of network traffic and analysis of anomalies can help detect suspicious activities that may indicate attempted attacks. Additionally, separating the IoT network from other networks, such as an office network, can limit the potential scope of an attack. Network segmentation reduces the risk that attackers who have taken control of one device can take control of the entire network. Data collected by IoT devices should be stored securely, with appropriate encryption mechanisms and access policies. It is also worth considering anonymizing data to reduce its value during unauthorized interception.

IoT systems are becoming increasingly complex, and security threats evolve as they develop. This requires continuously adapting security strategies and implementing modern technologies, such as artificial intelligence and machine learning, which can automatically identify and respond to threats in real time.

The urgency of establishing global security standards for IoT devices cannot be overstated. These standards are crucial to ensuring IoT devices’ safe and reliable operation, particularly in critical applications such as medicine, transportation, or industrial infrastructure.

Based on other reviews related to the use of the IoT in various areas of life and science and our findings, we can formulate the following remarks and observations:

• IoT-based monitoring and control systems have a positive impact on human life or the environment;
• Advancements in IoT and AI techniques improve the smart agriculture industry through disease identification, smart farm monitoring, and efficient data analysis;
• Combining IoT and AI technologies can enhance crop productivity, reduce costs, and reduce the ecological footprint of conventional farming (also based on [79,80,81,82]);
• IoT solutions may reduce hospitalization and overall healthcare spending by reducing readmissions (also based on [83,84,85]);
• Solutions and technologies used depend on the environment or industry sector in which they operate; we will use different sensors, actuators, or platforms in mining and different ones in agriculture or health care (also based on [44,86,87,88,89,90,91,92,93]);
• Incorporating specially designed IoT devices into smart city infrastructures can be challenging due to city dynamics (also based on [86,94,95,96]).

Moreover, we noticed that in almost all cited solutions and reviews, the authors highlighted challenges for IoT-based solutions, including technology complexity, privacy and security issues, underdeveloped infrastructure, and some limitations in technology adoption due to underdeveloped policies and mechanisms. So, security, privacy, trust, interoperability, data storage, and ownership and control are very desirable fields of development in IoT-based solutions. Other fields of development are connected with the following:

• Integration with AI methods that can improve convenience, time savings, and better quality of life;
• Wearable technologies that can bring many promising benefits and can significantly impact various aspects of our lives (health monitoring, supporting physical activity, assisting people with disabilities, etc.);
• Solutions to address environmental issues that will improve living in smart cities;
• Data management and edge, fog, and cloud computing platforms to manage data effectively and use it in practice.

As mentioned, the platforms and technologies used depend on the environment or industry sector in which they operate. The most typical platforms mentioned were Phytoprove, Telemetry2u, Sensoterra, Cropx, ONFARM, and Semios. Thus, the most used communication protocols were LoRaWAN, 6LowPAN, LTE, 4G, and ZigBee.

5. Conclusions

IoT technology is revolutionizing how we manage data and processes in various sectors of the economy. The article analyzes a variety of IoT-based monitoring and control systems applications, showing their significant impact on improving operational efficiency, reducing costs, and increasing the quality of services. In agriculture, the IoT allows for precise monitoring of soil and weather conditions, leading to irrigation optimization and increased yields. In healthcare, remote patient monitoring and medical equipment management enable more personalized and effective healthcare. In transport and logistics, the IoT improves shipment tracking, route optimization, and fleet management, which translates into better organization of supply chains. Smart cities use the IoT to manage urban infrastructure, improving residents’ quality of life through intelligent traffic management systems, street lighting, and air quality monitoring. In environmental protection, the IoT helps monitor natural resources and detect ecological threats, supporting sustainable development activities. Despite numerous benefits, implementing IoT systems also poses challenges. Data security, system interoperability, and scalability are significant barriers that must be overcome to exploit the potential of the IoT fully.

This article highlighted that although IoT-based monitoring and control systems are widely used, there is still much room for further development and improvement. Further research and innovation in this area will be vital to achieving a more sustainable, efficient, and secure future. The IoT has the potential to become the foundation of intelligent ecosystems, which will support the development of various economic sectors and improve the quality of life around the world.

Despite significant progress, many of these challenges remain open research problems, which require further work on developing new technologies and methods. The proposals for potential solutions presented in the article, such as the use of artificial intelligence, edge computing, or advanced cryptographic techniques, indicate possible directions of development that can help overcome existing barriers.

Future research in the IoT area should focus on further developing autonomous systems, ensuring security in the face of new threats, and on ethical and social aspects related to the widespread implementation of these technologies. Another important direction will be harmonizing standards and regulations, enabling broader integration, and the effective use of the IoT globally.

In summary, the future of IoT technology looks promising. IoT systems have enormous potential to revolutionize various sectors of the economy and everyday life. So, it is necessary to further research and develop technological solutions that will meet today’s challenges. However, further research, innovation, and collaboration at various levels are required to fully realize its potential and create intelligent ecosystems that support economic development and improve quality of life worldwide.