Search Results (28)

IoT applications for building energy management, enhanced by artificial intelligence (AI), have the potential to transform how energy is consumed, monitored, and optimized, especially in distributed energy systems. By using IoT sensors and smart meters, buildings can collect real-time data on energy usage patterns, occupancy, temperature, and lighting conditions.AI algorithms then analyze this data to identify inefficiencies, predict energy demand, and suggest or automate adjustments to optimize energy use. Integrating renewable energy sources, such as solar panels and wind turbines, into distributed systems uses IoT-based monitoring to ensure maximum efficiency in energy generation and use. These systems also enable dynamic energy pricing and load balancing, allowing buildings to participate in smart grids by storing or selling excess energy.AI-based predictive maintenance ensures that renewable energy systems, such as inverters and batteries, operate efficiently, minimizing downtime. The case studies show how IoT and AI are driving sustainable development by reducing energy consumption and carbon footprints in residential, commercial, and industrial buildings. Blockchain and IoT can further secure transactions and data in distributed systems, increasing trust, sustainability, and scalability. The combination of IoT, AI, and renewable energy sources is in line with global energy trends, promoting decentralized and greener energy systems. The case study highlights that adopting IoT and AI for energy management offers not only environmental benefits but also economic benefits, such as cost savings and energy independence. The best achieved accuracy was 0.8179 (RMSE 0.01). The overall effectiveness rating was 9/10; thus, AI-based IoT solutions are a feasible, cost-effective, and sustainable approach to office energy management. Full article

The exponential demand for real-time monitoring applications has altered the course of sensor development, from sensor electronics miniaturization, e.g., resorting to printing techniques, to low-cost, flexible and functional wearable materials. Humidity sensing has been used in the prevention and diagnosis of medical conditions, as well as in the assessment of physical comfort. This paper presents a resistive flexible humidity sensor composed of silver interdigitated electrodes (IDTs) screen printed onto polyimide film and an active layer of multiwall carbon nanotubes (MWCNT) dispersed in a water-soluble polymer, polyvinyl alcohol (PVA). Different MWCNT/PVA sensor sizes and MWCNT percentages are tested to study their effect on the initial electrical resistance (R_i) values and sensor response at different humidity percentages. The results show that the R_i values decrease with the increase in % MWCNT. The sensor size did not influence the sensor response, while the % MWCNT affected the sensor behavior upon relative humidity (RH) increments. The 1% MWCNT/PVA sensor showed the best response, reaching a relative electrical resistance, ΔR/R₀, of 509% at 99% RH. Comparable with other reported sensors, the produced MWCNT/PVA flexible sensor is simpler, greener and shows a good sensitivity to humidity, being easily incorporated in wearable monitoring applications, from sports to medical fields. Full article

Seafood, especially from the ocean, is now seen as a greener and more sustainable source of protein, causing an increase in its demand. This has also led to people making choices towards seafood as a replacement for carbon-intensive protein sources. As a result, the demand for seafood is growing, and as the aquaculture industry looks to increase production, keeping products safe and sustainable is imperative. There are many challenges faced by the aquaculture industry in meeting these increased demands. One such challenge is the presence of harmful algal blooms (HABs) in the ocean, which can have a major impact on aquatic life. In this paper, we look at the impact of this challenge on aquaculture and monitoring strategies whilst illustrating the potential for technological interventions to help mitigate the impact of an HAB. We will focus on Abagold Limited, a land-based marine aquaculture business that specialises in the large-scale production of abalone (Haliotis midae) based in Hermanus, South Africa. HABs are considered a threat to commercial-scale abalone farming along the South African coastline and require continuous monitoring. The most recent HAB was in February–April 2019, when the area experienced a severe red-tide event with blooms of predominantly Lingulodinium polyedrum. We present some of the monitoring strategies employing digital technologies to future-proof the industry. This article presents the development of a novel hybrid water quality forecasting model based on a TriLux multi-parameter sensor to monitor key water quality parameters. The actual experimental real water quality data from Abagold Limited show a good correlation as a basis for a forecasting model which would be a useful tool for the management of HABs in the aquaculture industry. Full article

Electronic waste (e-waste) contains toxic elements causing an important impact on environmental and human health. However, the presence of valuable metals, such as copper or gold, among others, make recycling a necessity for obtaining an alternative source of raw materials. Conventional metal recovery methods are environmentally unsound, prompting the exploration of greener alternatives like bioleaching, which utilizes the activity of microorganisms for a more sustainable recovery. However, the mechanisms involved in the process and the conditions to optimize the metabolic paths are still not completely known. Monitorization and automatization of the different stages composing the global process are crucial for advancing in the implementation of this novel technology at an industrial scale. For the first time, an open-source industrial IoT system is designed to enhance and regulate bioleaching by implementing real-time monitoring and control within the plant’s infrastructure. This system includes an Android app that displays real-time plant data from sensors and a robust server featuring a flexible application programming interface (API) for future applications. The app caters to specific needs such as remote sensor reading, actuator control, and real-time bioleaching alerts, ensuring secure access and proactive event management. By utilizing collected data, it minimizes downtime, equipment failures, and supply chain disruptions. The server maintains seamless communication with the plant controller, enabling efficient pump activation and sensor data transmission. A telegram bot demonstrates the API’s flexibility by forwarding plant alerts to users. During validation with concurrent remote user access, the application demonstrated its ability to prevent irreversible plant failures through an advanced alarm system. Ultimately, this IIoT system amplifies plant performance, safety, and efficiency by optimizing processes and decision-making capabilities. It emerges as a pivotal open-source tool, securing remote oversight and management of large-scale bioleaching plants, promising adaptability for future enhancements. Full article

Internet-of-Things systems are increasingly being installed in buildings to transform them into smart ones and to assist in the transition to a greener future. A common feature of smart buildings, whether commercial or residential, is environmental sensing that provides information about temperature, dust, and the general air quality of indoor spaces, assisting in achieving energy efficiency. Environmental sensors though, especially when combined, can also be used to detect occupancy in a space and to increase security and safety. The most popular methods for the combination of environmental sensor measurements are concatenation and neural networks that can conduct fusion in different levels. This work presents an evaluation of the performance of multiple late fusion methods in detecting occupancy from environmental sensors installed in a building during its construction and provides a comparison of the late fusion approaches with early fusion followed by ensemble classifiers. A novel weighted fusion method, suitable for imbalanced samples, is also tested. The data collected from the environmental sensors are provided as a public dataset. Full article

This bibliometric review elucidates the emerging intersection of Internet of Things (IoT) technologies and Green Stormwater Infrastructure (GSI), demonstrating the potential to reshape urban stormwater management. The study analyzes a steadily increasing corpus of literature since 2013, pointing out considerable international collaboration. Prominent contributions originate from the United States, Canada, Italy, China, and Australia, underscoring the global acknowledgement of the potential of IoT-enhanced GSI. Diverse GSI applications such as green roofs, smart rain barrels, bioretention systems, and stormwater detention ponds have demonstrated enhanced efficiency and real-time control with IoT integration. However, existing literature reveals several challenges, notably the requirement of advanced monitoring, the development of predictive optimization strategies, and extensive scalability. Comprehensive cost–benefit analyses are also critical for the widespread acceptance of IoT-integrated GSI. Current research addresses these challenges by exploring innovative strategies such as microbial-fuel-cell-powered soil moisture sensors and large-scale RTC bioretention systems. Emphasis is also on the need for security measures against potential digital threats. Future research needs to focus on real-time data-based monitoring plans, model validation, continuous optimization, and supportive policy frameworks. As the world confronts urban development, climate change, and aging infrastructure, IoT and GSI synergism presents a promising solution for effective stormwater management and enhancement of cultural ecosystem services. Continued exploration in this promising domain is crucial to pave the way for smarter, greener urban environments. Full article

The transition to sustainable or green(er) cities requires the development and implementation of many innovative technologies. It is vital to ensure that these technologies are themselves as sustainable and green as possible. In this context, smart materials offer excellent prospects for application. They are capable of performing a number of tasks (e.g., repair, opening/closing, temperature measurement, storage and release of thermal energy) without embedded electronics or power supplies. In this short review paper, we present some of the most promising smart material-based technologies for sustainable or green(er) cities. We will briefly present the state-of-the-art in smart concrete for the structural health monitoring and self-healing of civil engineering structures, phase-change materials (PCM) for passive air-conditioning, shape-memory materials (SMA) for various green applications, and meta-surfaces for green acoustics. To better illustrate the potential of some of the solutions discussed in the paper, we present, where appropriate, our most recent experimental results (e.g., embedded SAW sensors for the Structural Health Monitoring of concrete structures). The main aim of this paper is to promote green solutions based on smart materials to engineers and scientists involved in R&D projects for green(er) cities. Full article

The identification of an unknown gaseous species or the composition of a gaseous mixture can be performed using various experimental techniques such as: mass spectrometry, chromatography, nuclear magnetic resonance (NMR), infrared (IR), X-Rays, or by combining these analytical techniques (in automated analyzers). Unfortunately, these techniques use highly expensive equipment and require the use of qualified personnel. Using gas sensors is a viable and inexpensive alternative. The most commonly used sensors in the field are resistive type chemosensors (chemiresistors), due to their simple detection mechanism and low manufacturing costs. The detection principle of these sensors is based on the catalytic reaction between the sensitive material of the sensor and the target gas. This reaction occurs with the release or consumption of electrons, influencing the overall electrical resistance of the sensor. This review describes various MOX-based chemiresistors, which contain different types of sensitive substrates, such as powders, pellets or films, as well as a clear tendency towards sensor miniaturization and the constant improvement of the fabrication techniques towards greener and more cost-effective synthesis routes over time. The goal of this research was to obtain sensors with high 3S parameters (sensitivity, selectivity, and stability), that can be mass-produced and implemented on a wide scale. Full article

UAVs are sensor platforms increasingly used in precision agriculture, especially for crop and environmental monitoring using photogrammetry. In this work, light drone flights were performed on three consecutive days (with different weather conditions) on an experimental agricultural field to evaluate the photogrammetric performances due to colour calibration. Thirty random reconstructions from the three days and six different areas of the field were performed. The results showed that calibrated orthophotos appeared greener and brighter than the uncalibrated ones, better representing the actual colours of the scene. Parameter reporting errors were always lower in the calibrated reconstructions and the other quantitative parameters were always lower in the non-calibrated ones, in particular, significant differences were observed in the percentage of camera stations on the total number of images and the reprojection error. The results obtained showed that it is possible to obtain better orthophotos, by means of a calibration algorithm, to rectify the atmospheric conditions that affect the image obtained. This proposed colour calibration protocol could be useful when integrated into robotic platforms and sensors for the exploration and monitoring of different environments. Full article

Nowadays there is a growing concern with the environment and sustainability, which means that better methods, including pollutants analysis, with less consumption of materials, organic solvents, and energy, need to be developed. Considering the almost inexistent information about the topic, the main goal of this work was to compare the environmental impacts of two analytical methods, a traditional one based on liquid chromatography with fluorescence detection and a newly developed carbon paper sensor. The selected analyte was 17α-ethinylestradiol, which is a contaminant of emergent concern in aquatic ecosystems due to its endocrine disruptor behavior. The life cycle assessment data showed that the sensor detection presents an almost negligible environmental impact when compared with the extraction step (the same for both methods) and the liquid chromatographic determination (roughly 80 times higher than with the sensor). The sensor values for all categories of damage are below 3% of the total method impacts, i.e., 1.6, 1.9, 2.4, and 2.9% for resources, climate change, human health, and ecosystem quality. The extraction represents 98.1% of the sensor environmental impacts (and 99.6% of its life cycle costing) and 38.8% of the chromatographic method. This study evidences the need of developing and applying greener analytical (detection and extraction) strategies. Full article

The efficient and selective detection of volatile organic compounds (VOCs) provides key information for various purposes ranging from the toxicological analysis of indoor/outdoor environments to the diagnosis of diseases or to the investigation of biological processes. In the last decade, different sensors and biosensors providing reliable, rapid, and economic responses in the detection of VOCs have been successfully conceived and applied in numerous practical cases; however, the global necessity of a sustainable development, has driven the design of devices for the detection of VOCs to greener methods. In this review, the most recent and innovative VOC sensors and biosensors with sustainable features are presented. The sensors are grouped into three of the main industrial sectors of daily life, including environmental analysis, highly important for toxicity issues, food packaging tools, especially aimed at avoiding the spoilage of meat and fish, and the diagnosis of diseases, crucial for the early detection of relevant pathological conditions such as cancer and diabetes. The research outcomes presented in the review underly the necessity of preparing sensors with higher efficiency, lower detection limits, improved selectivity, and enhanced sustainable characteristics to fully address the sustainable manufacturing of VOC sensors and biosensors. Full article

In this work, template-free nanostructured conducting polymers (nCPs)-embedded gold nanoparticles (AuNPs) from aniline, thiophene and 3,4-ethylenedioxythiophene have been prepared via a one-pot sonochemical method. The synthesis of the nanocomposite (nCPs-AuNPs) was achieved in a short period of time (5–10 min), by applying high-energy ultrasound to an aqueous mixture of a CP precursor monomer and KAuCl₄, in the presence of LiClO₄ as dopant. The synthesis process is simpler, greener and faster in comparison to other procedures reported in the literature. Remarkably, bulk quantities of doped polyaniline PANI-AuNPs nanofibers were obtained. Subsequently, they were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS) and Fourier transform infrared spectroscopy (FTIR), as well as by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). PANI-AuNPs nanofibers were also employed as immobilization matrix for a benchmark enzyme, glucose oxidase (GOX). Finally, glucose was determined in real samples of white and red wines by using the so-obtained GOX-PANI-AuNPs/Sonogel-Carbon biosensor, providing outstanding recoveries (99.54%). This work may offer important insights into the synthesis of nanostructured conducting polymers and also stimulates the exploration of the applications of these nanocomposites, especially in research fields such as (bio)sensors, catalysis and composite materials. Full article

Energy efficiency generally implies the efficient use of energy in all sectors of final consumption—industry, services, agriculture, households and transport. Shipping accounts for nearly 3% of global greenhouse gas emissions, making it the sixth largest CO₂ producer in the world. This is a result of inefficient ship design, lack of planning and optimal use of resources. As the transport sector expands, so does the pressure for a greener and cleaner maritime industry. Reducing fuel consumption is a major driver of the need for energy efficiency on ships. In this paper, due to the importance of maritime transport, we observed the impact of reducing the dimensions of the main switchboard as a contribution to energy efficiency. This contribution is not of great importance as is the case with the optimization of the navigation route, etc., but it certainly affects the weight and, thus, the fuel consumption, which contributes to energy efficiency in the designed system. The aim of this paper is to optimize the design of the main switchboard by using 2D simulations of possible bus topologies, in order to develop six different busbar models and find one that best meets the requirements. The simulation results indicate the optimal location and dimensions of the busbars in the main switchboard in accordance with the switchgear parameters. Apart from the change in layout and dimensions of the busbars, the replacement of conventional instrument transformers with new current/voltage sensors contributes to a significant reduction in the weight and size of the switchboard, which ultimately benefits energy efficiency. Full article

Wireless sensor nodes (WSNs) are the fundamental part of an Internet of Things (IoT) system for detecting and transmitting data to a master node for processing. Several research studies reveal that one of the disadvantages of conventional, battery-powered WSNs, however, is that they typically require periodic maintenance. This paper aims to contribute to existing research studies on this issue by exploring a new energy-autonomous and battery-free WSN concept for monitor vibrations. The node is self-powered from the conversion of ambient mechanical vibration energy into electrical energy through a piezoelectric transducer implemented with lead-free lithium niobate piezoelectric material to also explore solutions that go towards a greener and more sustainable IoT. Instead of implementing any particular sensors, the vibration measurement system exploits the proportionality between the mechanical power generated by a piezoelectric transducer and the time taken to store it as electrical energy in a capacitor. This helps reduce the component count with respect to conventional WSNs, as well as energy consumption and production costs, while optimizing the overall node size and weight. The readout is therefore a function of the time it takes for the energy storage capacitor to charge between two constant voltage levels. The result of this work is a system that includes a specially designed lead-free piezoelectric vibrational transducer and a battery-less sensor platform with Bluetooth low energy (BLE) connectivity. The system can harvest energy in the acceleration range [0.5 g–1.2 g] and measure vibrations with a limit of detection (LoD) of 0.6 g. Full article

In this paper, an environmentally friendly inertial motion sensor is investigated, modelled, and characterized as an accelerometer. The sensor is obtained by using bacterial cellulose (BC) as a base biopolymer. BC is then impregnated with ionic liquids. Electrodes are realized by a conducting polymer, in a typical three-layer structure. The sensor works in a cantilever configuration and produces an open voltage signal as the result of a flexing deformation. A model is proposed for the transduction phenomenon. The composite mechano-electric transduction capability is exploited for realizing the accelerometer. Results of the chemical and transduction characterization of the accelerometer are reported. Finally, experimental evidence of the possible nature of the transduction phenomenon is given. Full article