Journal articles: 'Environmental sensors'

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Nistor, P., and I. Orha. "Environmental Parameters Monitoring System." Carpathian Journal of Electronic and Computer Engineering 14, no. 2 (December 1, 2021): 6–10. http://dx.doi.org/10.2478/cjece-2021-0007.

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Abstract The project presents the development of a system for monitoring environmental parameters. At the base of this system is the ESP-32S board that collects, processes and transmits data from the three sensors to the two web interfaces. The role of these web interfaces is to display the data collected from the sensors. The local web interface consists of two windows, the first window contains the table of sensors that displays the data measured by the sensors at that time. In the second window you can see the data measured by the sensors through graphs. They store the sensor data, giving the user the ability to view previously measured data. The local web interface provides sensor data only in the Wi-Fi network coverage area, and its data is deleted when the server is closed. The global web interface displays data using graphs. At the base of this web interface is the ThingSpeak platform that allows the system to transmit data anywhere in the world, store data in the Cloud space and the possibility of using special analysis functions.

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Mohamad Nor, Alif Syarafi, Mohd Amri Md. Yunus, Sophan Wahyudi, and Ibrahim Sallehhudin. "Low-Cost Sensors Array Based on Planar Electromagnetic Sensor Simulation for Environmental Monitoring." Advanced Materials Research 925 (April 2014): 614–18. http://dx.doi.org/10.4028/www.scientific.net/amr.925.614.

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Agriculture sectors have increased in sizes and numbers due to the expansion of human population. Human population growth has caused the demand in food, cloth, transportation, shelter etc. to increase tremendously. Essentially speaking, those surpluses of demands will adversely affect the production of agriculture sectors. In order to obtain high yield, the farmers might be overusing the fertilizer for their crops. These overused fertilizers will be dissolved in the nearest water resources such as river, pond and well. Hence, the natural water resources will be contaminated by these overused fertilizers. In this situation, there is a need for a sensor which could determine the contamination level in natural water resources. This project proposed low-cost sensor arrays based on planar electromagnetic sensors to monitor the contamination in the natural water resources. The sensors consist of three electromagnetic sensors that have been constructed in three types of configuration array namely, parallel, star, and delta. The modeling and simulation of the sensors were done by using COMSOL Multiphysics 4.2 software. Each sensor’s input was assign to 10 Volt peak to peak voltages and then the impedance of each sensor was obtained. In practical application, the impedance of these sensors will determine the contamination level of the water under test. The contamination condition was simulated by changing the electrical properties of the environment domain of the model that suit contamination condition. The impedance of each sensor was tabulated according to the increasing of frequency of the supply voltages. Hence, the best configuration of the planar electromagnetic sensors array for detection of contamination inside the natural water will be determined based on the sensitivity. This type of sensors will provide the in-situ measurement system which will save the cost and consequently the time required for each sample.

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Dean, Robert N., and Frank T. Werner. "A PCB Environmental Sensor for Use in Monitoring Drought Conditions in Estuaries." Journal of Microelectronics and Electronic Packaging 13, no. 4 (October 1, 2016): 182–87. http://dx.doi.org/10.4071/imaps.523.

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Estuaries occur in coastal regions worldwide and are important habitats for humans and other life forms. These fragile ecosystems are susceptible to the effects of prolonged drought conditions, resulting in changes in the salinity gradient across the estuary, which can adversely affect life forms living in and around the estuary. Electrical conductivity sensors are used to determine salinity of aqueous solutions, including water samples from estuaries. Conventional electrical conductivity sensors, consisting of orthogonally mounted thin parallel plate electrodes, are fragile and difficult to clean. Low-cost commercial printed circuit board technology is presented here as a vehicle to realize a robust planar sensor for determining salinity. This sensor's planar electrode configuration is inherently simpler and less fragile than a sensor with two orthogonally mounted thin parallel plate electrodes. Prototype planar sensors were designed, fabricated, and successfully tested in a freshwater-seawater solution ranging from 100% freshwater to 100% seawater, emulating the salinity levels encountered across many estuaries. The sensor test data demonstrated a linear characteristic with both conductance (R2 = 0.9995) and salinity (R2 = 0.9969) as a function of seawater concentration.

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Zareei, Mahdi, Cesar Vargas-Rosales, Mohammad Hossein Anisi, Leila Musavian, Rafaela Villalpando-Hernandez, Shidrokh Goudarzi, and Ehab Mahmoud Mohamed. "Enhancing the Performance of Energy Harvesting Sensor Networks for Environmental Monitoring Applications." Energies 12, no. 14 (July 20, 2019): 2794. http://dx.doi.org/10.3390/en12142794.

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Fast development in hardware miniaturization and massive production of sensors make them cost efficient and vastly available to be used in various applications in our daily life more specially in environment monitoring applications. However, energy consumption is still one of the barriers slowing down the development of several applications. Slow development in battery technology, makes energy harvesting (EH) as a prime candidate to eliminate the sensor’s energy barrier. EH sensors can be the solution to enabling future applications that would be extremely costly using conventional battery-powered sensors. In this paper, we analyze the performance improvement and evaluation of EH sensors in various situations. A network model is developed to allow us to examine different scenarios. We borrow a clustering concept, as a proven method to improve energy efficiency in conventional sensor network and brought it to EH sensor networks to study its effect on the performance of the network in different scenarios. Moreover, a dynamic and distributed transmission power management for sensors is proposed and evaluated in both networks, with and without clustering, to study the effect of power balancing on the network end-to-end performance. The simulation results indicate that, by using clustering and transmission power adjustment, the power consumption can be distributed in the network more efficiently, which result in improving the network performance in terms of a packet delivery ratio by 20%, 10% higher network lifetime by having more alive nodes and also achieving lower delay by reducing the hop-count.

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Duk-Dong Lee and Dae-Sik Lee. "Environmental gas sensors." IEEE Sensors Journal 1, no. 3 (2001): 214–24. http://dx.doi.org/10.1109/jsen.2001.954834.

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Gao, Rui, Wenjun Zhang, Junmin Jing, Zhiwei Liao, Zhou Zhao, Bin Yao, Huiyu Zhang, et al. "Design, Fabrication, and Dynamic Environmental Test of a Piezoresistive Pressure Sensor." Micromachines 13, no. 7 (July 19, 2022): 1142. http://dx.doi.org/10.3390/mi13071142.

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Microelectromechanical system (MEMS) pressure sensors have a wide range of applications based on the advantages of mature technology and easy integration. Among them, piezoresistive sensors have attracted great attention with the advantage of simple back-end processing circuits. However, less research has been reported on the performance of piezoresistive pressure sensors in dynamic environments, especially considering the vibrations and shocks frequently encountered during the application of the sensors. To address these issues, this paper proposes a design method for a MEMS piezoresistive pressure sensor, and the fabricated sensor is evaluated in a series of systematic dynamic environmental adaptability tests. After testing, the output sensitivity of the sensor chip was 9.21 mV∙bar−1, while the nonlinearity was 0.069% FSS. The sensor overreacts to rapidly changing pressure environments and can withstand acceleration shocks of up to 20× g. In addition, the sensor is capable of providing normal output over the vibration frequency range of 0–5000 Hz with a temperature coefficient sensitivity of −0.30% FSS °C−1 over the temperature range of 0–80 °C. Our proposed sensor can play a key role in applications with wide pressure ranges, high-frequency vibrations, and high acceleration shocks, as well as guide MEMS-based pressure sensors in high pressure ranges and complex environmental adaptability in their design.

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Caroleo, Fabrizio, Gabriele Magna, Mario Luigi Naitana, Lorena Di Zazzo, Roberto Martini, Francesco Pizzoli, Mounika Muduganti, et al. "Advances in Optical Sensors for Persistent Organic Pollutant Environmental Monitoring." Sensors 22, no. 7 (March 30, 2022): 2649. http://dx.doi.org/10.3390/s22072649.

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Optical chemical sensors are widely applied in many fields of modern analytical practice, due to their simplicity in preparation and signal acquisition, low costs, and fast response time. Moreover, the construction of most modern optical sensors requires neither wire connections with the detector nor sophisticated and energy-consuming hardware, enabling wireless sensor development for a fast, in-field and online analysis. In this review, the last five years of progress (from 2017 to 2021) in the field of optical chemical sensors development for persistent organic pollutants (POPs) is provided. The operating mechanisms, the transduction principles and the types of sensing materials employed in single selective optical sensors and in multisensory systems are reviewed. The selected examples of optical sensors applications are reported to demonstrate the benefits and drawbacks of optical chemical sensor use for POPs assessment.

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Azizi, Shoaib, Ramtin Rabiee, Gireesh Nair, and Thomas Olofsson. "Effects of Positioning of Multi-Sensor Devices on Occupancy and Indoor Environmental Monitoring in Single-Occupant Offices." Energies 14, no. 19 (October 2, 2021): 6296. http://dx.doi.org/10.3390/en14196296.

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The advancements in sensor and communication technologies drive the rapid developments in the applications of occupancy and indoor environmental monitoring in buildings. Currently, the installation standards for sensors are scarce and the recommendations for sensor positionings are very general. However, inadequate sensor positioning might diminish the reliability of sensor data, which could have serious impacts on the intended applications such as the performance of demand-controlled HVAC systems and their energy use. Thus, there is a need to understand how sensor positioning may affect the sensor data, specifically when using multi-sensor devices in which several sensors are being bundled together. This study is based on the data collected from 18 multi-sensor devices installed in three single-occupant offices (six sensors in each office). Each multi-sensor device included sensors to measure passive infrared (PIR) radiation, temperature, CO2, humidity, and illuminance. The results show that the positions of PIR and CO2 sensors significantly affect the reliability of occupancy detection. The typical approach of positioning the sensors on the ceiling, in the middle of offices, may lead to relatively unreliable data. In this case, the PIR sensor in that position has only 60% accuracy of presence detection. Installing the sensors under office desks could increase the accuracy of presence detection to 84%. These two sensor positions are highlighted in sensor fusion analysis as they could reach the highest accuracy compared to other pairs of PIR sensors. Moreover, sensor positioning can affect various indoor environmental parameters, especially temperature and illuminance measurements.

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Antunes, Alex. "Cheap Deployable Networked Sensors for Environmental Use." Journal of Telecommunications and the Digital Economy 2, no. 4 (May 26, 2020): 15. http://dx.doi.org/10.18080/jtde.v2n4.271.

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We profile the utility and limits in deployment of inexpensive disposable sensor networks by amateurs to achieve environmental monitoring goals. Four current technology movements — PC-on-a-chip processors such as Arduino, prebuilt sensors, 3-D printing, and Wi-Fi and mesh networking — enable rapid sensor platform creation and make it easy for non-specialists to create general sensor-bearing platforms. Deployment of a cluster of multiple sensor-bearing platforms is, however, communications-limited in terms of both range and number of devices supported, and generally requires a base station with internet access. We examine how inexpensive technology supports scenarios for short-term environmental modelling by average citizens.

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Buček, Pavel, Petr Maršolek, and Jiří Bílek. "Low-Cost Sensors for Air Quality Monitoring - the Current State of the Technology and a Use Overview." Chemistry-Didactics-Ecology-Metrology 26, no. 1-2 (December 1, 2021): 41–54. http://dx.doi.org/10.2478/cdem-2021-0003.

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Abstract In recent years the monitoring of air quality using cheap sensors has become an interesting alternative to conventional analytical techniques. Apart from vast price differences conventional techniques need to be performed by the trained personnel of commercial or research laboratories. Sensors capable of measuring dust, ozone, nitrogen and sulphur oxides, or other air pollutants are relatively simple electronic devices, which are comparable in size to a mobile phone. They provide the general public with the possibility to monitor air quality which can contribute to various projects that differ in regional scale, commercial funding or community-base. In connection with the low price of sensors arises the question of the quality of measured data. This issue is addressed by a number of studies focused on comparing the sensor data with the data of reference measurements. Sensory measurement is influenced by the monitored analyte, type and design of the particular sensor, as well as by the measurement conditions. Currently sensor networks serve as an additional source of information to the network of air quality monitoring stations, where the density of the network provides concentration trends in the area that may exceed specific measured values of pollutant concentrations and low uncertainty of reference measurements. The constant development of all types of sensors is leading to improvements and the difference in data quality between sensors and conventional monitoring techniques may be reduced.

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Singh, Ravinder, and Kuldeep Singh Nagla. "Comparative analysis of range sensors for the robust autonomous navigation – a review." Sensor Review 40, no. 1 (October 29, 2019): 17–41. http://dx.doi.org/10.1108/sr-01-2019-0029.

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Purpose The purpose of this research is to provide the necessarily and resourceful information regarding range sensors to select the best fit sensor for robust autonomous navigation. Autonomous navigation is an emerging segment in the field of mobile robot in which the mobile robot navigates in the environment with high level of autonomy by lacking human interactions. Sensor-based perception is a prevailing aspect in the autonomous navigation of mobile robot along with localization and path planning. Various range sensors are used to get the efficient perception of the environment, but selecting the best-fit sensor to solve the navigation problem is still a vital assignment. Design/methodology/approach Autonomous navigation relies on the sensory information of various sensors, and each sensor relies on various operational parameters/characteristic for the reliable functioning. A simple strategy shown in this proposed study to select the best-fit sensor based on various parameters such as environment, 2 D/3D navigation, accuracy, speed, environmental conditions, etc. for the reliable autonomous navigation of a mobile robot. Findings This paper provides a comparative analysis for the diverse range sensors used in mobile robotics with respect to various aspects such as accuracy, computational load, 2D/3D navigation, environmental conditions, etc. to opt the best-fit sensors for achieving robust navigation of autonomous mobile robot. Originality/value This paper provides a straightforward platform for the researchers to select the best range sensor for the diverse robotics application.

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Shimojima, Koji, Toshio Fukuda, Fumihito Arai, and Hideo Matsuura. "Multi-Sensor Integration System utilizing Fuzzy Inference and Neural Network." Journal of Robotics and Mechatronics 4, no. 5 (October 20, 1992): 416–21. http://dx.doi.org/10.20965/jrm.1992.p0416.

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Sensors are important for recognizing the system state environmental status in the intelligent robotic system. Thus, the sensor integration system (SIS) has been studied in a wide range of applications. In this paper, it is shown that the SIS can expand the measurable region of sensors with higher accuracy by multiple sensors and that operators can use the system as easily as a single high-performance sensor system. Systems which have been reported so far do not have flexibility for changing/replacing sensors. Thus, this paper presents an approach to the SIS with the knowledge data base of sensors, so the proposed SIS has the flexibility for changing/replacing sensors. This system consists of four subsystems: 1) sensors as hardware sensing devices, 2) knowledge data base of sensors (KBS), 3) fuzzy inference, and 4) neural network(NN). This system can estimate the error for the sensor’s measured value by fuzzy inference with KBS. The measured values are integrated by NN. The inferred error and measured value are put into NN. Then, NN’s output gives the integrated value of multiple sensors. The proposed system is shown to be effective through extensive experiments.

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Huang, Qian, and Kane Rodriguez. "A Software Framework for Heterogeneous Wireless Sensor Network Towards Environmental Monitoring." Applied Sciences 9, no. 5 (February 28, 2019): 867. http://dx.doi.org/10.3390/app9050867.

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A wireless sensor network (WSN) is typically composed of spatially distributed miniature sensors that help collect large amounts of real-time environmental data from buildings. These environmental data (e.g., temperature, humidity, CO2 concentration) can assist a series of heating, ventilation, and air conditioning (HVAC) equipment to increase the building energy efficiency. From a system design perspective, heterogeneous wireless sensor networks need to address two challenges. First, sensor data acquisition, conversion, fusion, and packaging involve a series of software processing. Since each type of environmental sensor typically has unique processing requirements, it is difficult to develop an efficient software framework to combine the processing of multiple heterogeneous sensors. Second, during normal operation of a heterogeneous wireless sensor network, if users insert or remove some environmental sensors, the entire WSN system should operate normally. In this work, in order to solve the above two system design challenges, we have developed a low-power, low-cost, small form-factor WSN development platform, and its software framework can perform efficient data acquisition, conversion, fusion, and packaging for multiple heterogeneous sensors. Our proposed software framework enables easy and rapid WSN system deployment without affecting the overall functionality of each node. The proposed design differs from existing WSN platforms in that it emphasizes advanced high-level usability and reduces time to market without sacrificing low-level features. The proposed WSN system has been implemented and tested in an office building for indoor fire hazard detection. The experimental results show that our software framework can successfully complete data acquisition, conversion, fusion, and packaging tasks for three heterogeneous environmental sensors. In addition, we have verified that our software framework supports robust system operation when inserting or removing sensors from an existing heterogeneous WSN system.

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Vasiljevic, Dragana, Cedo Zlebic, Goran Stojanovic, Mitar Simic, Libu Manjakkal, and Zoran Stamenkovic. "Cost-effective sensors and sensor nodes for monitoring environmental parameters." Facta universitatis - series: Electronics and Energetics 31, no. 1 (2018): 11–23. http://dx.doi.org/10.2298/fuee1801011v.

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This paper reviews the design and characterization of humidity and pH sensors manufactured in the printed circuit board (PCB), ink-jet, and screen printing technologies. The first one (PCB technology) provides robust sensors with PET film which can be exposed to harsh environment. The second (ink-jet technology) can manufacture sensors on flexible substrates (foils and papers). The third (screen printing technology) has been used to implement a thick-film sensor. In addition to this, a multi-sensor cloud-based electronic system with autonomous power supply (solar panels) for air and water quality monitoring has been described. Finally, a flexible and modular hardware platform for remote and reliable sensing of environmental parameters has been presented.

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Skinner, William S., Sunny Zhang, Robert E. Guldberg, and Keat Ghee Ong. "Magnetoelastic Sensor Optimization for Improving Mass Monitoring." Sensors 22, no. 3 (January 22, 2022): 827. http://dx.doi.org/10.3390/s22030827.

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Magnetoelastic sensors, typically made of magnetostrictive and magnetically-soft materials, can be fabricated from commercially available materials into a variety of shapes and sizes for their intended applications. Since these sensors are wirelessly interrogated via magnetic fields, they are good candidates for use in both research and industry, where detection of environmental parameters in closed and controlled systems is necessary. Common applications for these sensors include the investigation of physical, chemical, and biological parameters based on changes in mass loading at the sensor surface which affect the sensor’s behavior at resonance. To improve the performance of these sensors, optimization of sensor geometry, size, and detection conditions are critical to increasing their mass sensitivity and detectible range. This work focuses on investigating how the geometry of the sensor influences its resonance spectrum, including the sensor’s shape, size, and aspect ratio. In addition to these factors, heterogeneity in resonance magnitude was mapped for the sensor surface and the effect of the magnetic bias field strength on the resonance spectrum was investigated. Analysis of the results indicates that the shape of the sensor has a strong influence on the emergent resonant modes. Reducing the size of the sensor decreased the sensor’s magnitude of resonance. The aspect ratio of the sensor, along with the bias field strength, was also observed to affect the magnitude of the signal; over or under biasing and aspect ratio extremes were observed to decrease the magnitude of resonance, indicating that these parameters can be optimized for a given shape and size of magnetoelastic sensor.

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Honeycutt, Wesley T., M. Tyler Ley, and Nicholas F. Materer. "Precision and Limits of Detection for Selected Commercially Available, Low-Cost Carbon Dioxide and Methane Gas Sensors." Sensors 19, no. 14 (July 18, 2019): 3157. http://dx.doi.org/10.3390/s19143157.

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The performance of a sensor platform for environmental or industrial monitoring is sensitive to the cost and performance of the individual sensor elements. Thus, the detection limits, accuracy, and precision of commercially available, low-cost carbon dioxide and methane gas concentration sensors were evaluated by precise measurements at known gas concentrations. Sensors were selected based on market availability, cost, power consumption, detection range, and accuracy. A specially constructed gas mixing chamber, coupled to a precision bench-top analyzer, was used to characterize each sensor during a controlled exposure to known gas concentrations. For environmental monitoring, the selected carbon dioxide sensors were characterized around 400 ppm. For methane, the sensor response was first monitored at 0 ppm, close to the typical environmental background. The selected sensors were then evaluated at gas concentrations of several thousand ppm. The determined detection limits accuracy, and precision provides a set of matrices that can be used to evaluate and select sensors for integration into a sensor platform for specific applications.

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Ho, Clifford, and M. Schöning. "Sensors for Environmental Monitoring." Sensors 5, no. 1 (January 28, 2005): 1–3. http://dx.doi.org/10.3390/s5010001.

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Harnett, Cindy. "Nanotechnology in environmental sensors." IEEE Instrumentation & Measurement Magazine 13, no. 2 (April 2010): 8–12. http://dx.doi.org/10.1109/mim.2010.5438331.

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Fu, Liling, Panagiotis Dallas, Virender K. Sharma, and Kewei Zhang. "Sensors for Environmental Monitoring." Journal of Sensors 2016 (2016): 1. http://dx.doi.org/10.1155/2016/4108790.

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Wang, Libing, Wei Ma, Liguang Xu, Wei Chen, Yingyue Zhu, Chuanlai Xu, and Nicholas A. Kotov. "Nanoparticle-based environmental sensors." Materials Science and Engineering: R: Reports 70, no. 3-6 (November 2010): 265–74. http://dx.doi.org/10.1016/j.mser.2010.06.012.

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Roozeboom, Clifton L., Matthew A. Hopcroft, Wesley S. Smith, Joo Yong Sim, David A. Wickeraad, Peter G. Hartwell, and Beth L. Pruitt. "Integrated Multifunctional Environmental Sensors." Journal of Microelectromechanical Systems 22, no. 3 (June 2013): 779–93. http://dx.doi.org/10.1109/jmems.2013.2245400.

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Omolaja, Adebola, Abayomi Otebolaku, and Ali Alfoudi. "Context-Aware Complex Human Activity Recognition Using Hybrid Deep Learning Models." Applied Sciences 12, no. 18 (September 16, 2022): 9305. http://dx.doi.org/10.3390/app12189305.

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Smart devices, such as smartphones, smartwatches, etc., are examples of promising platforms for automatic recognition of human activities. However, it is difficult to accurately monitor complex human activities on these platforms due to interclass pattern similarities, which occur when different human activities exhibit similar signal patterns or characteristics. Current smartphone-based recognition systems depend on traditional sensors, such as accelerometers and gyroscopes, which are built-in in these devices. Therefore, apart from using information from the traditional sensors, these systems lack the contextual information to support automatic activity recognition. In this article, we explore environmental contexts, such as illumination (light conditions) and noise level, to support sensory data obtained from the traditional sensors using a hybrid of Convolutional Neural Network and Long Short-Term Memory (CNN–LSTM) learning models. The models performed sensor fusion by augmenting low-level sensor signals with rich contextual data to improve the models’ recognition accuracy and generalization. Two sets of experiments were performed to validate the proposed solution. The first set of experiments used triaxial inertial sensing signals to train baseline models, while the second set of experiments combined the inertial signals with contextual information from environmental sensors. The obtained results demonstrate that contextual information, such as environmental noise level and light conditions using hybrid deep learning models, achieved better recognition accuracy than the traditional baseline activity recognition models without contextual information.

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Tanikawa, Tamio, Kenichi Ohara, and Kohtaro Ohba. "Structural environmental informatization using sensor network with heterogeneous sensors." Intelligent Service Robotics 3, no. 1 (November 28, 2009): 21–28. http://dx.doi.org/10.1007/s11370-009-0055-6.

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Linevych, Yaroslav Oleksiiovych, and Viktoriia Mykhailivna Koval. "Sensors Based on Nanoscale Silicon 1D Structures for Industrial, Environmental and Medical Monitoring." Microsystems, Electronics and Acoustics 27, no. 2 (August 21, 2022): 264376–1. http://dx.doi.org/10.20535/2523-4455.mea.264376.

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Article is devoted to the analysis of modern sensors based on silicon nanowires (SiNWs) to determine the influence of SiNWs synthesis parameters and their structural features on device characteristics. A modern trend in the development of electronic sensing devices is the use of various types of nanomaterials in order to increase sensor sensitivity and miniaturize of their size. 1D nanomaterials, namely SiNWs, have several advantages for sensor applications, such as a large surface-to-volume ratio and an increased rate of diffusion of the main charge carriers. Based on the literature analysis, an overview of modern SiNWs sensors was made. The advantages of silicon 1D structures were shown by comparison with other types of nanostructures. Also sensors were classified according to the methods of synthesis of SiNWs, sensor principle operation, kind of input value and types of applied modifiers. Silicon nanowires were most often synthesized by the method of metal-stimulated chemical etching, the advantages of which include the simplicity of implementation, low cost, and the ability to synthesize nanostructures with a high aspect ratio. The vapor-liquid-solid synthesis was also used, the advantages of which include the ability to be adapted to any technology of supplying a gas mixture with the target component and the possibility of obtaining nanowires with a diameter of 10 nm or less. According to the principle operation, the most of sensors developed on the basis of silicon nanowires are of electrical type (resistive, capacitive, electrochemical, diode or transistor type), optical sensors (fluorescent) are developed to a much lesser extent. Gas sensors (ethanol, oil vapor, formaldehyde, ammonia, nitrogen oxide, hydrogen, carbon dioxide,), liquid sensors (glucose, hydrogen peroxide, ethanol, heavy metal ions, pH), and physical values (humidity, temperature and illumination) have been developed on the basis of silicon 1D nanoscale structures. The following surface modifiers of nanowires were used to improve the performance characteristics: noble metal nanoparticles, metal-organic framework structures, carbon nanotubes, graphene, self-assembled monolayers, metal and metal oxide thin films. In particular, it was shown that the modification of the surface of the array of SiNWs with noble metals led to an increase in the sensitivity of the hydrogen sensor by 80%. Modification of formaldehyde sensor using reduced graphene oxide resulted in an improvement of sensor sensitivity by more than 2 times. The influence of SiNWs synthesis parameters on sensor performance characteristics was also determined. In particular, it was shown that increasing of SiNWs width from 20–30 nm to 500–600 nm led to an increase in the sensitivity of humidity sensor from 4.5 to 7.5%. Increasing the etching time caused the synthesis of longer nanowires, which improved the sensitivity of carbon dioxide sensors from 0.6 to 2.5%. Dependences established in this work will make it possible to develop the production technology of various types of sensors based on silicon nanowires with high sensitivity, selectivity, stability and operation speed.

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Tomić, Josif, Miloš B. Živanov, Miodrag Kušljević, Đorđe Obradović, and József Szatmari. "Realization of Measurement Station for Remote Environmental Monitoring." Key Engineering Materials 543 (March 2013): 105–8. http://dx.doi.org/10.4028/www.scientific.net/kem.543.105.

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The greenhouse effect is a naturally occurring process that heats the Earth's surface and atmosphere. It is a result of the fact that certain atmospheric gases, such as carbon dioxide, water vapor, and methane, are able to change the energy balance of the planet by absorbing long wave radiation emitted from the Earth's surface. Number of gases are involved in the human caused enhancement of the greenhouse effect. Carbon dioxide is the most important gas of these gases, which contributes about 55% of the change in the intensity of the Earth's greenhouse effect. The global monitoring of the greenhouse gases is necessary for handling the global warming issue. This paper presents a practical implementation of a measurement station for environmental monitoring using Internet technology and large sensor networks. The application of the sensor networks in the environmental monitoring requires the development specific solutions. This paper presents a solution that relies on existing technology, but offers hardware and software upgrade due to the advantages of using the concept of virtual instrumentation. The application uses temperature sensors, air relative humidity sensors, gas sensors and others. The measurement station collects the data from the sensors and sends them to the users using the UDP protocol via the Internet and GPRS modem. The measurement station was implemented in LabVIEW programming package.

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Evstigneev, V. P., P. N. Kuznetsov, D. Y. Voronin, and V. A. Naumova. "Variant analysis of measurement components in environmental engineering." IOP Conference Series: Earth and Environmental Science 981, no. 3 (February 1, 2022): 032030. http://dx.doi.org/10.1088/1755-1315/981/3/032030.

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Abstract Modern environmental engineering requires innovative approaches to intellectual monitoring. There is a need for a large number of geographically distributed measuring modules that have sufficient measurement accuracy for environmental engineering and, at the same time, requiring low financial investment. One of the most important stages of such work is the selection of the optimal sensors that meet these requirements. The article presents the results of parallel measurements of environmental parameters using a set of sensors BME280, AHT20, DHT22 and standard meteorological observations. The BME280 sensor demonstrated the best quality of the reproduction of the parameters. The study was carried out using the developed test bench for the integrated monitoring of meteorological parameters, which allows comparative testing of several sensors with data transmission to a WEB server.

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Capote Mastrapa, Gil, and Fernando Lazaro Freire. "Plasma-Treated CVD Graphene Gas Sensor Performance in Environmental Condition: The Role of Defects on Sensitivity." Journal of Sensors 2019 (November 4, 2019): 1–7. http://dx.doi.org/10.1155/2019/5492583.

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In this work, a low-cost resistive gas sensor based on graphene grown by CVD was fabricated and its sensitivity was studied in terms of defect density. CVD graphene was transferred using Polyurethane as sacrifice layer with low contamination and defect-free results. An atmospheric plasma etching system was used to homogeneously induce defects on the sensor’s active area, as investigated through Raman spectroscopy. Device sensing properties were significantly enhanced for greater defect density for both NH3 and NO2. The modified sensors were submitted to different concentrations of both target gas to assess detection limits and overall behavior. It was revealed that defective CVD graphene devices possess sensitivity up to ppm range with linear dependence in the range of values measured. The fabricated sensors presented little to no signal degradation after months of atmospheric exposure.

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Pearlshtien, Daniela Heller, Stefano Pignatti, and Eyal Ben-Dor. "Vicarious CAL/VAL Approach for Orbital Hyperspectral Sensors Using Multiple Sites." Remote Sensing 15, no. 3 (January 29, 2023): 771. http://dx.doi.org/10.3390/rs15030771.

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The hyperspectral (HSR) sensors Earth Surface Mineral Dust Source Investigation (EMIT) of the National Aeronautics and Space Administration (NASA) and Environmental Mapping and Analysis Program (EnMAP) of the German Aerospace Center (DLR) were recently launched. These state-of-the-art sensors have joined the already operational HSR sensors DESIS (DLR), PRISMA (Italian Space Agency), and HISUI (developed by the Japanese Ministry of Economy, Trade, and Industry METI and Japan Aerospace Exploration Agency JAXA). The launching of more HSR sensors is being planned for the near future (e.g., SBG of NASA, and CHIME of the European Space Agency), and the challenge of monitoring and maintaining their calibration accuracy is becoming more relevant. We proposed two test sites: Amiaz Plain (AP) and Makhtesh Ramon (MR) for spectral, radiometric, and geometric calibration/validation (CAL/VAL). The sites are situated in the arid environment of southern Israel and are in the same overpass coverage. Both test sites have already demonstrated favorable results in assessing an HSR sensor’s performance and were chosen to participate in the EMIT and EnMAP validation stage. We first evaluated the feasibility of using AP and MR as CAL/VAL test sites with extensive datasets and sensors, such as the multispectral sensor Landsat (Landsat5 TM and Landsat8 OLI), the airborne HSR sensor AisaFENIX 1K, and the spaceborne HSR sensors DESIS and PRISMA. Field measurements were taken over time. The suggested methodology integrates reflectance and radiometric CAL/VAL test sites into one operational protocol. The method can highlight degradation in the spectral domain early on, help maintain quantitative applications, adjust the sensor’s radiometric calibration during its mission lifetime, and minimize uncertainties of calibration parameters. A PRISMA sensor case study demonstrates the complete operational protocol, i.e., performance evaluation, quality assessment, and cross-calibration between HSR sensors. These CAL/VAL sites are ready to serve as operational sites for other HSR sensors.

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Skrzetuska, Ewa, and Jarosław Wojciechowski. "Investigation of the Impact of Environmental Parameters on Breath Frequency Measurement by a Textile Sensor." Sensors 20, no. 4 (February 21, 2020): 1179. http://dx.doi.org/10.3390/s20041179.

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The aim of this work was to develop sensors that enable the monitoring of respiratory frequencies and will be competitive at a global level in replacing conventional electronic sensors based on rigid and uncomfortable materials. The preliminary work carried out showed the real possibility of creating flat fibrous products containing carbon nanotubes with sensory properties. Bearing in mind the production of a textile deformation sensor, textile materials with high elasticity and deformation reversibility were used in the preliminary studies. The authors assumed that it would be possible to conduct registration associated with the measurement of pneumography continuously in various atmospheric conditions and with varying intensification of human physical activity. The conducted experiment allows us to state that the resistance at the level of 10 kΩ is sufficient to collect results of breathing frequency at rest and after physical effort.

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Veeramuthu, Loganathan, Manikandan Venkatesan, Fang-Cheng Liang, Jean-Sebastien Benas, Chia-Jung Cho, Chin-Wen Chen, Ye Zhou, Rong-Ho Lee, and Chi-Ching Kuo. "Conjugated Copolymers through Electrospinning Synthetic Strategies and Their Versatile Applications in Sensing Environmental Toxicants, pH, Temperature, and Humidity." Polymers 12, no. 3 (March 5, 2020): 587. http://dx.doi.org/10.3390/polym12030587.

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Conjugated copolymers (CCPs) are a class of polymers with excellent optical luminescent and electrical conducting properties because of their extensive π conjugation. CCPs have several advantages such as facile synthesis, structural tailorability, processability, and ease of device fabrication by compatible solvents. Electrospinning (ES) is a versatile technique that produces continuous high throughput nanofibers or microfibers and its appropriate synchronization with CCPs can aid in harvesting an ideal sensory nanofiber. The ES-based nanofibrous membrane enables sensors to accomplish ultrahigh sensitivity and response time with the aid of a greater surface-to-volume ratio. This review covers the crucial aspects of designing highly responsive optical sensors that includes synthetic strategies, sensor fabrication, mechanistic aspects, sensing modes, and recent sensing trends in monitoring environmental toxicants, pH, temperature, and humidity. In particular, considerable attention is being paid on classifying the ES-based optical sensor fabrication to overcome remaining challenges such as sensitivity, selectivity, dye leaching, instability, and reversibility.

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Rasshofer, R. H., and K. Gresser. "Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions." Advances in Radio Science 3 (May 12, 2005): 205–9. http://dx.doi.org/10.5194/ars-3-205-2005.

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Abstract. Automotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001). Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar sensors available on the market today suffer from low angular resolution and poor target detection in medium ranges (30 to 60m) over azimuth angles larger than ±30°. In contrast, Lidar sensors show large sensitivity towards environmental influences (e.g. snow, fog, dirt). Both sensor technologies today have a rather high cost level, forbidding their wide-spread usage on mass markets. A common approach to overcome individual sensor drawbacks is the employment of data fusion techniques (Bar-Shalom, 2001). Raw data fusion requires a common, standardized data interface to easily integrate a variety of asynchronous sensor data into a fusion network. Moreover, next generation sensors should be able to dynamically adopt to new situations and should have the ability to work in cooperative sensor environments. As vehicular function development today is being shifted more and more towards virtual prototyping, mathematical sensor models should be available. These models should take into account the sensor's functional principle as well as all typical measurement errors generated by the sensor.

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Alharbi, Raed, Mehrdad Irannejad, and Mustafa Yavuz. "A Short Review on the Role of the Metal-Graphene Hybrid Nanostructure in Promoting the Localized Surface Plasmon Resonance Sensor Performance." Sensors 19, no. 4 (February 19, 2019): 862. http://dx.doi.org/10.3390/s19040862.

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Localized Surface Plasmon Resonance (LSPR) sensors have potential applications in essential and important areas such as bio-sensor technology, especially in medical applications and gas sensors in environmental monitoring applications. Figure of Merit (FOM) and Sensitivity (S) measurements are two ways to assess the performance of an LSPR sensor. However, LSPR sensors suffer low FOM compared to the conventional Surface Plasmon Resonance (SPR) sensor due to high losses resulting from radiative damping of LSPs waves. Different methodologies have been utilized to enhance the performance of LSPR sensors, including various geometrical and material parameters, plasmonic wave coupling from different structures, and integration of noble metals with graphene, which is the focus of this report. Recent studies of metal-graphene hybrid plasmonic systems have shown its capability of promoting the performance of the LSPR sensor to a level that enhances its chance for commercialization. In this review, fundamental physics, the operation principle, and performance assessment of the LSPR sensor are presented followed by a discussion of plasmonic materials and a summary of methods used to optimize the sensor’s performance. A focused review on metal-graphene hybrid nanostructure and a discussion of its role in promoting the performance of the LSPR sensor follow.

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Lin, Xueer, Jiaying Luo, Minyan Liao, Yalan Su, Mo Lv, Qing Li, Shenglan Xiao, and Jianbang Xiang. "Wearable Sensor-Based Monitoring of Environmental Exposures and the Associated Health Effects: A Review." Biosensors 12, no. 12 (December 6, 2022): 1131. http://dx.doi.org/10.3390/bios12121131.

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Recent advances in sensor technology have facilitated the development and use of personalized sensors in monitoring environmental factors and the associated health effects. No studies have reviewed the research advancement in examining population-based health responses to environmental exposure via portable sensors/instruments. This study aims to review studies that use portable sensors to measure environmental factors and health responses while exploring the environmental effects on health. With a thorough literature review using two major English databases (Web of Science and PubMed), 24 eligible studies were included and analyzed out of 16,751 total records. The 24 studies include 5 on physical factors, 19 on chemical factors, and none on biological factors. The results show that particles were the most considered environmental factor among all of the physical, chemical, and biological factors, followed by total volatile organic compounds and carbon monoxide. Heart rate and heart rate variability were the most considered health indicators among all cardiopulmonary outcomes, followed by respiratory function. The studies mostly had a sample size of fewer than 100 participants and a study period of less than a week due to the challenges in accessing low-cost, small, and light wearable sensors. This review guides future sensor-based environmental health studies on project design and sensor selection.

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Liu, Ze Liang, and Ning Li Liang. "Design of Crop Environmental Monitoring System Based on ZigBee." Advanced Materials Research 546-547 (July 2012): 1171–75. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.1171.

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A large number of sensors have been used in the system to form a monitoring network through ZigBee protocol. The system can obtain the information through these sensors, and according to the information the position in question will be accurately located. The sensors connect to the monitoring network through a wireless module, and upload monitoring information in real time. The gateway is responsible for receiving the wireless sensor nodes to data storage, display and management, to achieve all base test point access to information, management, dynamic display and analysis and processing. This information will be display to the user with charts and text prompt manner in the monitoring software and it provides a variety of sound and light alarm information and message alarm information.

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Butt, Muhammad A., Grigory S. Voronkov, Elizaveta P. Grakhova, Ruslan V. Kutluyarov, Nikolay L. Kazanskiy, and Svetlana N. Khonina. "Environmental Monitoring: A Comprehensive Review on Optical Waveguide and Fiber-Based Sensors." Biosensors 12, no. 11 (November 17, 2022): 1038. http://dx.doi.org/10.3390/bios12111038.

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Globally, there is active development of photonic sensors incorporating multidisciplinary research. The ultimate objective is to develop small, low-cost, sensitive, selective, quick, durable, remote-controllable sensors that are resistant to electromagnetic interference. Different photonic sensor designs and advances in photonic frameworks have shown the possibility to realize these capabilities. In this review paper, the latest developments in the field of optical waveguide and fiber-based sensors which can serve for environmental monitoring are discussed. Several important topics such as toxic gas, water quality, indoor environment, and natural disaster monitoring are reviewed.

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Whitehill, Andrew R., Russell W. Long, Shawn P. Urbanski, Maribel Colón, Andrew Habel, and Matthew S. Landis. "Evaluation of Cairpol and Aeroqual Air Sensors in Biomass Burning Plumes." Atmosphere 13, no. 6 (May 28, 2022): 877. http://dx.doi.org/10.3390/atmos13060877.

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Cairpol and Aeroqual air quality sensors measuring CO, CO2, NO2, and other species were tested on fresh biomass burning plumes in field and laboratory environments. We evaluated the sensors by comparing 1 min sensor measurements to collocated reference instrument measurements. The sensors were evaluated based on the coefficient of determination (r2) between the sensor and reference measurements, as well as by the accuracy, collocated precision, root mean square error (RMSE), and other metrics. In general, CO and CO2 sensors performed well (in terms of accuracy and r2 values) compared to NO2 sensors. Cairpol CO and NO2 sensors had better sensor-versus-sensor agreement (i.e., collocated precision) than Aeroqual CO and NO2 sensors of the same species. Tests of other sensors (e.g., NH3, H2S, VOC, and NMHC) provided more inconsistent results and need further study. Aeroqual NO2 sensors had an apparent O3 interference that was not observed in the Cairpol NO2 sensors. Although the sensor accuracy lags that of reference-level monitors, with location-specific calibrations they have the potential to provide useful data about community air quality and personal exposure to smoke impacts.

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Li, Ming, Scott K. Cushing, and Nianqiang Wu. "Plasmon-enhanced optical sensors: a review." Analyst 140, no. 2 (2015): 386–406. http://dx.doi.org/10.1039/c4an01079e.

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This paper presents a critical review of recent research progress in plasmonic sensors, plasmon-enhanced fluorescence sensors, and surface-enhanced Raman scattering sensors. It places emphasis on the sensor design strategies, and highlights the applications of sensors in healthcare, homeland security, food safety and environmental monitoring.

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Chen, Shuai, Zexu Xue, Nan Gao, Xiaomei Yang, and Ling Zang. "Perylene Diimide-Based Fluorescent and Colorimetric Sensors for Environmental Detection." Sensors 20, no. 3 (February 9, 2020): 917. http://dx.doi.org/10.3390/s20030917.

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Perylene tetracarboxylic diimide (PDI) and its derivatives exhibit excellent thermal, chemical and optical stability, strong electron affinity, strong visible-light absorption and unique fluorescence on/off features. The combination of these features makes PDIs ideal molecular frameworks for development in a broad range of sensors for detecting environmental pollutants such as heavy metal ions (e.g., Cu2+, Cd2+, Hg2+, Pd2+, etc.), inorganic anions (e.g., F−, ClO4−, PO4−, etc.), as well as poisonous organic compounds such as nitriles, amines, nitroaromatics, benzene homologues, etc. In this review, we provide a comprehensive overview of the recent advance in research and development of PDI-based fluorescent sensors, as well as related colorimetric and multi-mode sensor systems, for environmental detection in aqueous, organic or mixed solutions. The molecular design of PDIs and structural optimization of the sensor system (regarding both sensitivity and selectivity) in response to varying analytes are discussed in detail. At the end, a perspective summary is provided covering both the key challenges and potential solutions for the future development of PDI-based optical sensors.

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Mena, Alma Rosa, Hector G. Ceballos, and Joanna Alvarado-Uribe. "Measuring Indoor Occupancy through Environmental Sensors: A Systematic Review on Sensor Deployment." Sensors 22, no. 10 (May 16, 2022): 3770. http://dx.doi.org/10.3390/s22103770.

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The COVID-19 pandemic has changed our common habits and lifestyle. Occupancy information is valued more now due to the restrictions put in place to reduce the spread of the virus. Over the years, several authors have developed methods and algorithms to detect/estimate occupancy in enclosed spaces. Similarly, different types of sensors have been installed in the places to allow this measurement. However, new researchers and practitioners often find it difficult to estimate the number of sensors to collect the data, the time needed to sense, and technical information related to sensor deployment. Therefore, this systematic review provides an overview of the type of environmental sensors used to detect/estimate occupancy, the places that have been selected to carry out experiments, details about the placement of the sensors, characteristics of datasets, and models/algorithms developed. Furthermore, with the information extracted from three selected studies, a technique to calculate the number of environmental sensors to be deployed is proposed.

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Singh, Ravinder, and Kuldeep Singh Nagla. "A modified sensor fusion framework for quantifying and removing the effect of harsh environmental condition for reliable mobile robot mapping." Sensor Review 39, no. 4 (July 15, 2019): 456–72. http://dx.doi.org/10.1108/sr-10-2018-0272.

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Purpose An autonomous mobile robot requires efficient perception of the environment to perform various tasks in a challenging environment. The precise sensory information from the range sensors is required to accomplish prerequisites, such as SLAM, path planning and localization. But the accuracy and precision of the sensors become unreliable in harsh environmental conditions because of the effect of rain, dust, humidity, fog and smoke. The purpose of this paper is to generate robust mapping of the environment in harsh environmental conditions. Design/methodology/approach This paper presents a novel technique, averaging data with short range selection (ADWSRS), to reduce the effect of harsh environmental (rain, wind, humidity, etc.) conditions on sensory information (range) to generate reliable grid mapping. The sensory information on laser and sonar sensors in terms of probability values (occupied/unoccupied cell) in generating grid maps are fused after passing through two newly designed pre-processing filters: laser averaging filter and short range selection filter. This proposed approach relies on various aspects such as averaging laser data analogous to current pose of the sensor, selection of short range with respect to threshold value to remove the effect of specular reflection/crosstalk of sonar and a newly designed apparatus in which dirt cover (glass cover) and air blower are coupled to remove the influence of dirt, rain and humidity. Findings This proposed approach is tested in different environmental conditions, and to verify the consistency of the proposed approach, qualitative and quantitative analyses are carried out, which shows 42.5 per cent improvement in the probability value of occupied cells in the generated grid map. Originality/value The proposed ADWSRS approach reduced the effect of harsh environmental conditions such as fog, rain and smoke to generate efficient mapping of the environment, which may be implemented in diverse applications such as autonomous navigation, localization, path planning and mapping.

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Chandran, Sajith Kumar. "NANOMATERIAL SENSORS FOR ENVIRONMENTAL POLLUTANTS." Journal of Advanced Scientific Research 12, no. 03 (August 31, 2021): 42–49. http://dx.doi.org/10.55218/jasr.202112306.

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Nowadays, global environment of water, soil, and atmospheric systems has continuously been deteriorating due to the incessant release of toxic chemicals from various constructed sources. The existence of heavy metal ions in the environment poses serious threats to human health and the ecosystem. Therefore, this review focuses on the advent of nanotechnology that has given immense opportunities for developing advanced nanomaterials with unique functionalities. This review reports on the development of sensing techniques based on nanomaterials including metal and metal oxide nanomaterials, quantum dots, carbon nanomaterials and polymer nanocomposites. Nanomaterials well possess excellent electrical, optical, thermal, catalytic properties and strong mechanical strength, which offer great opportunities to construct nanomaterials-based sensors or devices for environmental pollutants. The nanosorbents themselves should be nontoxic, the sorbents present relatively high sorption capacities and selectivity to the low concentration of pollutants. The adsorbed pollutants can be removed from the surface of the nanoadsorbent easily and sorbents infinitely recycled.

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Kim, Younghun, and Byunghwan Lee. "Propectives of Environmental Colorimetric-Sensors." Korean Chemical Engineering Research 49, no. 4 (August 1, 2011): 393–99. http://dx.doi.org/10.9713/kcer.2011.49.4.393.

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Yang, Yang, and Zhiqun Daniel Deng. "Stretchable sensors for environmental monitoring." Applied Physics Reviews 6, no. 1 (March 2019): 011309. http://dx.doi.org/10.1063/1.5085013.

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Karube, Isao, and Yoko Nomura. "Enzyme sensors for environmental analysis." Journal of Molecular Catalysis B: Enzymatic 10, no. 1-3 (October 2000): 177–81. http://dx.doi.org/10.1016/s1381-1177(00)00125-9.

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Meixner, H., J. Gerblinger, and M. Fleischer. "Sensors for monitoring environmental pollution." Sensors and Actuators B: Chemical 15, no. 1-3 (August 1993): 45–54. http://dx.doi.org/10.1016/0925-4005(93)85026-7.

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Niessner, R. "Chemical sensors for environmental analysis." TrAC Trends in Analytical Chemistry 10, no. 10 (November 1991): 310–16. http://dx.doi.org/10.1016/0165-9936(91)87006-r.

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Cespedes, E. R., and C. E. Kolb. "SPECTROSCOPIC ENVIRONMENTAL TRACE SPECIES SENSORS." Optics and Photonics News 9, no. 8 (August 1, 1998): 38. http://dx.doi.org/10.1364/opn.9.8.000038.

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Owen, Valerie M. "USA - single molecule environmental sensors." Biosensors and Bioelectronics 11, no. 8 (January 1996): xxi. http://dx.doi.org/10.1016/0956-5663(96)85949-5.

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Becker, Anna Maria, Heike Marquart, Torsten Masson, Carolin Helbig, and Uwe Schlink. "Impacts of Personalized Sensor Feedback Regarding Exposure to Environmental Stressors." Current Pollution Reports 7, no. 4 (December 2021): 579–93. http://dx.doi.org/10.1007/s40726-021-00209-0.

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AbstractFeedback on personal exposure to air pollution, noise or extreme temperatures through wearable sensors or sensors installed at home or in the workplace can offer information that might motivate behaviours to mitigate exposure. As personal measurement devices are becoming increasingly accessible, it is important to evaluate the effects of such sensors on human perception and behaviour. We conducted a systematic literature research and identified 33 studies, analysing the effects of personal feedback on air pollution, noise and temperatures. Feedback was given through reports including different forms of visualization, in-person or over the telephone, or directly on the sensor or through a phone app. The exposure feedback led to behaviour changes particularly for noise and temperature feedback while findings on behaviour adaptation to avoid air pollution were mixed. Most studies reported increased awareness and knowledge from receiving exposure feedback. Many participants in studies on air pollution reported low levels of self-efficacy regarding exposure mitigation. For a better understanding of the effects of personal exposure feedback, more studies are required, particularly providing feedback from wearable sensors measuring outdoor air pollution, noise and temperature.

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Balde, Alpha Yaya, Emmanuel Bergeret, Denis Cajal, and Jean-Pierre Toumazet. "Low Power Environmental Image Sensors for Remote Photogrammetry." Sensors 22, no. 19 (October 8, 2022): 7617. http://dx.doi.org/10.3390/s22197617.

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This paper aims to prove the feasibility of a 4D monitoring solution (3D modeling and temporal monitoring) for the sandbar and to characterize the species’ role in the landscape. The developed solution allows studying the interaction between the river dynamics and vegetation using a network of low resolution and low power sensors. The issues addressed concern the feasibility of implementing a photogrammetry solution using low-resolution sensors as well as the choice of the appropriate sensor and its testing according to different configurations (image capture and storage on the sensor and/or image transmission to a centralization node) and also the detailed analysis of the different phases of the process (camera initialization, image capture, network transmission and selection of the most appropriate standby mode). We reveal that the tiny, low-cost board (ESP32-Cam) can perform a 3D reconstruction and propose using the camera’s UXGA (1600, 1200) resolution because of the quality rendering and energy consumption. A multi-node scenario based on a combined Wi-Fi and GSM relay is proposed in the study showing several years of autonomy for the system. Finally, to illustrate the energy cost of the module, we have defined a study process, where we have identified and quantified one by one the different phases of operation of the card for better energy optimization (setup, camera configuration, shooting, saving on SD card, or sending by Wi-Fi). The device is now operational for deployment on the Allier River (France).

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Journal articles on the topic 'Environmental sensors'

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