Journal articles on the topic 'COTS and low-cost sensor'
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Jakub, Lev, Shapoval Vadym, Bartoška Jan, and Kumhála František. "Low-cost infrared sensor for wildlife detection in vegetation." Research in Agricultural Engineering 63, Special Issue (December 22, 2017): S13—S17. http://dx.doi.org/10.17221/32/2017-rae.
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The protection of wild animals from mutilation or being killed during haymaking is still a serious problem connected with high working speeds and widths of modern harvesting machines. That is why the main aim of this study was to test low-cost, high-speed and low-noise infrared array sensor Melexis MLX90621 for the application of wildlife detection with the potential to be used in front of the mower equipment. The tests with two different crops with or without a hidden dog were made. Results showed that the sensor is able to detect an animal hidden in the crop with very high probability. Nevertheless, direct sunlight conditions can cause the problems when using infrared technology. A simultaneous use of other sensors working on different principle than infrared technology can be thus recommended.
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Ranđelović, Dušan, Goran Vorotović, Aleksandar Bengin, and Pavle Petrović. "Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors." FME Transactions 49, no. 1 (2021): 21–28. http://dx.doi.org/10.5937/fme2101021r.
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The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor.
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Adla, Soham, Neeraj Kumar Rai, Sri Harsha Karumanchi, Shivam Tripathi, Markus Disse, and Saket Pande. "Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors." Sensors 20, no. 2 (January 8, 2020): 363. http://dx.doi.org/10.3390/s20020363.
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Soil volumetric water content ( V W C ) is a vital parameter to understand several ecohydrological and environmental processes. Its cost-effective measurement can potentially drive various technological tools to promote data-driven sustainable agriculture through supplemental irrigation solutions, the lack of which has contributed to severe agricultural distress, particularly for smallholder farmers. The cost of commercially available V W C sensors varies over four orders of magnitude. A laboratory study characterizing and testing sensors from this wide range of cost categories, which is a prerequisite to explore their applicability for irrigation management, has not been conducted. Within this context, two low-cost capacitive sensors—SMEC300 and SM100—manufactured by Spectrum Technologies Inc. (Aurora, IL, USA), and two very low-cost resistive sensors—the Soil Hygrometer Detection Module Soil Moisture Sensor (YL100) by Electronicfans and the Generic Soil Moisture Sensor Module (YL69) by KitsGuru—were tested for performance in laboratory conditions. Each sensor was calibrated in different repacked soils, and tested to evaluate accuracy, precision and sensitivity to variations in temperature and salinity. The capacitive sensors were additionally tested for their performance in liquids of known dielectric constants, and a comparative analysis of the calibration equations developed in-house and provided by the manufacturer was carried out. The value for money of the sensors is reflected in their precision performance, i.e., the precision performance largely follows sensor costs. The other aspects of sensor performance do not necessarily follow sensor costs. The low-cost capacitive sensors were more accurate than manufacturer specifications, and could match the performance of the secondary standard sensor, after soil specific calibration. SMEC300 is accurate ( M A E , R M S E , and R A E of 2.12%, 2.88% and 0.28 respectively), precise, and performed well considering its price as well as multi-purpose sensing capabilities. The less-expensive SM100 sensor had a better accuracy ( M A E , R M S E , and R A E of 1.67%, 2.36% and 0.21 respectively) but poorer precision than the SMEC300. However, it was established as a robust, field ready, low-cost sensor due to its more consistent performance in soils (particularly the field soil) and superior performance in fluids. Both the capacitive sensors responded reasonably to variations in temperature and salinity conditions. Though the resistive sensors were less accurate and precise compared to the capacitive sensors, they performed well considering their cost category. The YL100 was more accurate ( M A E , R M S E , and R A E of 3.51%, 5.21% and 0.37 respectively) than YL69 ( M A E , R M S E , and R A E of 4.13%, 5.54%, and 0.41, respectively). However, YL69 outperformed YL100 in terms of precision, and response to temperature and salinity variations, to emerge as a more robust resistive sensor. These very low-cost sensors may be used in combination with more accurate sensors to better characterize the spatiotemporal variability of field scale soil moisture. The laboratory characterization conducted in this study is a prerequisite to estimate the effect of low- and very low-cost sensor measurements on the efficiency of soil moisture based irrigation scheduling systems.
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Sunny, Ali Imam, Aobo Zhao, Li Li, and Sambu Kanteh Kanteh Sakiliba. "Low-Cost IoT-Based Sensor System: A Case Study on Harsh Environmental Monitoring." Sensors 21, no. 1 (December 31, 2020): 214. http://dx.doi.org/10.3390/s21010214.
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Wireless Sensor Networks (WSNs) are promising technologies for exploiting in harsh environments such as can be found in the nuclear industry. Nuclear storage facilities can be considered harsh environments in that, amongst other variables, they can be dark, congested, and have high gamma radiation levels, which preclude operator access. These conditions represent significant challenges to sensor reliability, data acquisition and communications, power supplies, and longevity. Installed monitoring of parameters such as temperature, pressure, radiation, humidity, and hydrogen content within a nuclear facility may offer significant advantages over current baseline measurement options. This paper explores Commercial Off-The-Shelf (COTS) components to comprise an installed Internet of Things (IoT)-based multipurpose monitoring system for a specific nuclear storage situation measuring hydrogen concentration and temperature. This work addresses two major challenges of developing an installed remote sensing monitor for a typical nuclear storage scenario to detect both hydrogen concentrations and temperature: (1) development of a compact, cost-effective, and robust multisensor system from COTS components, and (2) validation of the sensor system for detecting temperature and hydrogen gas release. The proof of concept system developed in this study not only demonstrates the cost reduction of regular monitoring but also enables intelligent data management through the IoT by using ThingSpeak in a harsh environment.
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Chacón-Mateos, Miriam, Bernd Laquai, Ulrich Vogt, and Cosima Stubenrauch. "Evaluation of a low-cost dryer for a low-cost optical particle counter." Atmospheric Measurement Techniques 15, no. 24 (December 22, 2022): 7395–410. http://dx.doi.org/10.5194/amt-15-7395-2022.
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Abstract. The use of low-cost sensors for air quality measurements has become very popular in the last few decades. Due to the detrimental effects of particulate matter (PM) on human health, PM sensors like photometers and optical particle counters (OPCs) are widespread and have been widely investigated. The negative effects of high relative humidity (RH) and fog events in the mass concentration readings of these types of sensors are well documented. In the literature, different solutions to these problems – like correction models based on the Köhler theory or machine learning algorithms – have been applied. In this work, an air pre-conditioning method based on a low-cost thermal dryer for a low-cost OPC is presented. This study was done in two parts. The first part of the study was conducted in the laboratory to test the low-cost dryer under two different scenarios. In one scenario, the drying efficiency of the low-cost dryer was investigated in the presence of fog. In the second scenario, experiments with hygroscopic aerosols were done to determine to which extent the low-cost dryer reverts the growth of hygroscopic particles. In the second part of the study, the PM10 and PM2.5 mass concentrations of an OPC with dryer were compared with the gravimetric measurements and a continuous federal equivalent method (FEM) instrument in the field. The feasibility of using univariate linear regression (ULR) to correct the PM data of an OPC with dryer during field measurement was also evaluated. Finally, comparison measurements between an OPC with dryer, an OPC without dryer, and a FEM instrument during a real fog event are also presented. The laboratory results show that the sensor with the low-cost dryer at its inlet measured an average of 64 % and 59 % less PM2.5 concentration compared with a sensor without the low-cost dryer during the experiments with fog and with hygroscopic particles, respectively. The outcomes of the PM2.5 concentrations of the low-cost sensor with dryer in laboratory conditions reveal, however, an excess of heating compared with the FEM instrument. This excess of heating is also demonstrated in a more in-depth study on the temperature profile inside the dryer. The correction of the PM10 concentrations of the sensor with dryer during field measurements by using ULR showed a reduction of the maximum absolute error (MAE) from 4.3 µg m−3 (raw data) to 2.4 µg m−3 (after correction). The results for PM2.5 make evident an increase in the MAE after correction: from 1.9 µg m−3 in the raw data to 3.2 µg m−3. In light of these results, a low-cost thermal dryer could be a cost-effective add-on that could revert the effect of the hygroscopic growth and the fog in the PM readings. However, special care is needed when designing a low-cost dryer for a PM sensor to produce FEM similar PM readings, as high temperatures may irreversibly change the sampled air by evaporating the most volatile particulate species and thus deliver underestimated PM readings. New versions of a low-cost dryer aiming at FEM measurements should focus on maintaining the RH at the sensor inlet at 50 % and avoid reaching temperatures higher than 40 ∘C in the drying system. Finally, we believe that low-cost dryers have a very promising future for the application of sensors in citizen science, sensor networks for supplemental monitoring, and epidemiological studies.
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Liu, Chang, Stephen D. Prior, and James P. Scanlan. "Design and Implementation of a Low Cost Mini Quadrotor for Vision Based Maneuvers in GPS Denied Environments." Unmanned Systems 04, no. 03 (July 2016): 185–96. http://dx.doi.org/10.1142/s2301385016500059.
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This paper presents the design and implementation detail of an advanced mini quadrotor system, including the low cost commercial-off-the-shelf (COTS) electronics and advanced control algorithm. The proposed quadrotor has a gross takeoff weight of 758[Formula: see text]g and 360[Formula: see text]mm frame diagonal size. It is capable of semi-autonomous maneuver in GPS denied environments, solely relying on onboard sensors and computers. A globally defined quadrotor model is formularized, and a nonlinear velocity tracking controller is implemented on the special Euclidean group SE(3). An optical flow and ultrasonic-based onboard downward-facing camera is used as the primary sensor to provide velocity and altitude measurement feedback for the controller. The control and sensor fusion algorithm is developed under Arduino compatible open source electronics.
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Catsamas, Stephen, Baiqian Shi, Boris Deletic, Miao Wang, and David T. McCarthy. "A Low-Cost, Low-Power Water Velocity Sensor Utilizing Acoustic Doppler Measurement." Sensors 22, no. 19 (September 30, 2022): 7451. http://dx.doi.org/10.3390/s22197451.
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Current commercial sensors to monitor water flow velocities are expensive, bulky, and require significant effort to install. Low-cost sensors open the possibility of monitoring storm and waste water systems at a much greater spatial and temporal resolution without prohibitive costs and resource investment. To aid in this, this work developed a low-cost, low-power velocity sensor based on acoustic Doppler velocimetry. The sensor, costing less than 50 USD is open-source, open-hardware, compact, and easily interfaceable to a wide range of data-logging systems. A freely available sensor design at this price point does not currently exist, and its novelty is in enabling high-resolution real-time monitoring schemes. The design is capable of measuring water velocities up to 1200 mm/s. The sensor is characterised and then verified in an in-field long-term test. Finally, the data from this test are then used to evaluate the performance of the sensor in a real-world scenario. The analysis concludes that the sensor is capable of effectively measuring water velocity.
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Schwamback, Dimaghi, Magnus Persson, Ronny Berndtsson, Luis Eduardo Bertotto, Alex Naoki Asato Kobayashi, and Edson Cezar Wendland. "Automated Low-Cost Soil Moisture Sensors: Trade-Off between Cost and Accuracy." Sensors 23, no. 5 (February 22, 2023): 2451. http://dx.doi.org/10.3390/s23052451.
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Automated soil moisture systems are commonly used in precision agriculture. Using low-cost sensors, the spatial extension can be maximized, but the accuracy might be reduced. In this paper, we address the trade-off between cost and accuracy comparing low-cost and commercial soil moisture sensors. The analysis is based on the capacitive sensor SKU:SEN0193 tested under lab and field conditions. In addition to individual calibration, two simplified calibration techniques are proposed: universal calibration, based on all 63 sensors, and a single-point calibration using the sensor response in dry soil. During the second stage of testing, the sensors were coupled to a low-cost monitoring station and installed in the field. The sensors were capable of measuring daily and seasonal oscillations in soil moisture resulting from solar radiation and precipitation. The low-cost sensor performance was compared to commercial sensors based on five variables: (1) cost, (2) accuracy, (3) qualified labor demand, (4) sample volume, and (5) life expectancy. Commercial sensors provide single-point information with high reliability but at a high acquisition cost, while low-cost sensors can be acquired in larger numbers at a lower cost, allowing for more detailed spatial and temporal observations, but with medium accuracy. The use of SKU sensors is then indicated for short-term and limited-budget projects in which high accuracy of the collected data is not required.
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Lane, David W. "X-ray imaging and spectroscopy using low cost COTS CMOS sensors." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 284 (August 2012): 29–32. http://dx.doi.org/10.1016/j.nimb.2011.09.007.
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Sabatini, Anna, Alessandro Zompanti, Simone Grasso, Luca Vollero, Giorgio Pennazza, and Marco Santonico. "Proof of Concept Study of an Electrochemical Sensor for Inland Water Monitoring with a Network Approach." Remote Sensing 13, no. 20 (October 9, 2021): 4026. http://dx.doi.org/10.3390/rs13204026.
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The technologies most suitable for monitoring the ecosystem of inland waters are image spectrometry and electrochemical sensors. The reason is that these instruments are able to ensure accuracy in the surveillance of very large areas through reliable and frequent measurements performed remotely. Electrochemical systems provide low-cost, miniaturized, reliable sensors that can be organized, when equipped with commercial on the shelf (COTS) low-power radio components implementing LoRaWAN, Sigfox or NB-IoT communications, in a dense network of sensors achieving the aforementioned requirements. In this work, a low-cost, low-size and low-noise electrochemical sensor endowed with protocols for network configuration, management and monitoring is presented. The electronic interface of the sensor allows high reproducible responses. As proof of concept for its utilization in inland water monitoring, the device has been tested for water composition analysis, bacteria identification and frequent pollutant detection: atrazine, dichloromethane and tetrachloroethene. The results are promising, and future investigations will be oriented to unlock the true potential of a general-purpose approach exploiting the continuous fusion of distributed data in each of the three considered application scenarios. A new device, with reduced power consumption and size, has been also developed and tested; this new device should be a node of a large network for inland water monitoring.
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Sutar, Kirankumar. "LOW COST WIRELESS WEATHER MONITORING SYSTEM." International Journal of Engineering Technologies and Management Research 1, no. 1 (January 29, 2020): 35–39. http://dx.doi.org/10.29121/ijetmr.v1.i1.2015.24.
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Weather monitoring holds great importance and have uses in several areas ranging from keeping track of agricultural field weather conditions to industrial conditions monitoring. Weather monitoring plays an important role in human life, so the collection of information about weather changes is very important. This paper describes a weather monitoring system which enables the monitoring of weather parameters like Temperature, Humidity and Light intensity. Sensor module includes the sensors like temperature, humidity and light sensor. The system is developed using ZigBee wireless module. The measured weather parameters are Temperature, Humidity and Light intensity. The developed system is cost effective, compact and portable.
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García, Jesús A., Evangelina Lara, and Leocundo Aguilar. "A Low-Cost Calibration Method for Low-Cost MEMS Accelerometers Based on 3D Printing." Sensors 20, no. 22 (November 12, 2020): 6454. http://dx.doi.org/10.3390/s20226454.
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A ubiquitous sensor in embedded systems is the accelerometer, as it enables a range of applications. However, accelerometers experience nonlinearities in their outputs caused by error terms and axes misalignment. These errors are a major concern because, in applications such as navigations systems, they accumulate over time, degrading the position accuracy. Through a calibration procedure, the errors can be modeled and compensated. Many methods have been proposed; however, they require sophisticated equipment available only in laboratories, which makes them complex and expensive. In this article, a simple, practical, and low-cost calibration method is proposed. It uses a 3D printed polyhedron, benefiting from the popularisation and low-cost of 3D printing in the present day. Additionally, each polyhedron could hold as much as 14 sensors, which can be calibrated simultaneously. The method was performed with a low-cost sensor and it significantly reduced the root-mean-square error (RMSE) of the sensor output. The RMSE was compared with the reported in similar proposals, and our method resulted in higher performance. The proposal enables accelerometer calibration at low-cost, and anywhere and anytime, not only by experts in laboratories. Compensating the sensor’s inherent errors thus increases the accuracy of its output.
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Bean, Jeffrey K. "Evaluation methods for low-cost particulate matter sensors." Atmospheric Measurement Techniques 14, no. 11 (November 25, 2021): 7369–79. http://dx.doi.org/10.5194/amt-14-7369-2021.
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Abstract. Understanding and improving the quality of data generated from low-cost sensors represent a crucial step in using these sensors to fill gaps in air quality measurement and understanding. This paper shows results from a 10-month-long campaign that included side-by-side measurements and comparison between reference instruments approved by the United States Environmental Protection Agency (EPA) and low-cost particulate matter sensors in Bartlesville, Oklahoma. At this rural site in the Midwestern United States the instruments typically encountered only low (under 20 µg m−3) concentrations of particulate matter; however, higher concentrations (50–400 µg m−3) were observed on 3 different days during what were likely agricultural burning events. This study focused on methods for understanding and improving data quality for low-cost particulate matter sensors. The data offered insights on how averaging time, choice of reference instrument, and the observation of higher pollutant concentrations can all impact performance indicators (R2 and root mean square error) for an evaluation. The influence of these factors should be considered when comparing one sensor to another or when determining whether a sensor can produce data that fit a specific need. Though R2 and root mean square error remain the dominant metrics in sensor evaluations, an alternative approach using a prediction interval may offer more consistency between evaluations and a more direct interpretation of sensor data following an evaluation. Ongoing quality assurance for sensor data is needed to ensure that data continue to meet expectations. Observations of trends in linear regression parameters and sensor bias were used to analyze calibration and other quality assurance techniques.
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Al Smadi. "Low Cost Smart Sensor Design." American Journal of Engineering and Applied Sciences 4, no. 1 (January 1, 2011): 162–68. http://dx.doi.org/10.3844/ajeassp.2011.162.168.
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Rudolf, F., and H. de Lambilly. "Low-cost pressure sensor microsystem." Microsystem Technologies 1, no. 2 (March 1995): 84–87. http://dx.doi.org/10.1007/bf01624468.
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Báthory, Csongor, Márton L. Kiss, Attila Trohák, Zsolt Dobó, and Árpád Bence Palotás. "Preliminary research for low-cost particulate matter sensor network." E3S Web of Conferences 100 (2019): 00004. http://dx.doi.org/10.1051/e3sconf/201910000004.
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Low-cost particulate matter (PM) sensors may be suitable for indicative air quality measurements thanks to their small dimensions and high spatial resolution. Three different sensor types were selected for investigation in this study with specific focus on a Honeywell HPMA115S0 sensor to find out its usability at outdoors, perform load and long-term tests. The load test showed that the sensor calculates PM10 based on measured PM2.5 values. The analysis shows a break in calculation method at 25 μg/m3 PM2.5, and the calculation method for PM10 varies from 25 μg/m3 by around 81 μg/m3. Parallel test performed with different sensor types has shown that the protective cover formed by lamellar exterior does not affect the accuracy of the sensors, no accumulation or loss of sensitivity occurs. Long-term measurements have shown that the concentration values measured by the Honeywell sensor during outdoor measurements require humidity compensation, over 90% relative humidity (RH) the Pearson correlation coefficient (R) between the reference and sensor PM2.5 concentrations decreased by 0.3.
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Gong, Yandong, Ke Li, and Zhuo Zhang. "Investigation on Low Cost Optical Fiber Sensor Interrogator." Instruments and Experimental Techniques 64, no. 5 (September 2021): 765–67. http://dx.doi.org/10.1134/s002044122106004x.
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Abstract— Optical fiber sensor is attracting more attention in the structural health monitoring of civil applications. A general interrogator which can be used for both SOFO and fiber Bragg grating (FBG) sensors has been proposed, it has a lower cost with a much simpler design. Its accuracy can reach up to ~2.5 με, it has a niche market where it can compete with the conventional sensors.
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Murtiyoso, A., P. Grussenmeyer, and D. Suwardhi. "TECHNICAL CONSIDERATIONS IN LOW-COST HERITAGE DOCUMENTATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17 (November 29, 2019): 225–32. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w17-225-2019.
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Abstract. The use of photogrammetry in 3D heritage documentation has matured over the recent years. In the same time, many types of sensors have also been developed in the field of imaging. While photogrammetry is considered as a low-cost alternative to TLS, several options exist in terms of sensor type with trade-offs between price, ease of use, and quality of resolution. Nevertheless, a proper knowledge on the acquisition and processing is still required to generate acceptable results. This paper aims to compare three photogrammetric sensors, namely a classical DSLR camera, a drone, and a spherical 360° camera in documenting heritage sites. Main comparison points include quality of the bundle adjustment and quality of the dense point cloud. However, an important point of the paper is also to determine whether a sensor at a given cost and effort is enough for documentation purposes. A TLS point cloud data was used as a common reference, as well as control and check points issued from geodetic surveying. In the aftermath of the comparison, several technical suggestions and recommendations were proposed as regards to the use of each sensor.
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Awaludin, Lukman, and Oktaf Agni Dhewa. "Low Cost Sensor Node Device for Monitoring Landslides." IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) 8, no. 2 (October 31, 2018): 201. http://dx.doi.org/10.22146/ijeis.39682.
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Landslides are one of the natural disasters that often occur in Indonesia. Therefore, this disaster cannot be eliminated, but it can minimize the disadvantage caused by an early warning mechanism. Early warning systems rely on a sensor node used to read soil conditions with specific parameters. Those parameters that are read lead to the detection of mass movements. With the tightness of the monitoring process, of course, a reliable sensor node is needed. However, there are challenges in how to minimize losses that occur due to damage to sensor nodes when landslides occur. Sensor nodes are made using IMU sensors to monitor mass movements and its use two processors, namely microcontroller and mini SBC, which are inexpensive to manufacture and do not require large space in the installation.
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Shen, Xiaoyu, Yuntian Teng, and Xingxing Hu. "Design of a Low-Cost Small-Size Fluxgate Sensor." Sensors 21, no. 19 (October 2, 2021): 6598. http://dx.doi.org/10.3390/s21196598.
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Traditional fluxgate sensors used in geomagnetic field observations are large, costly, power-consuming and often limited in their use. Although the size of the micro-fluxgate sensors has been significantly reduced, their performance, including indicators such as accuracy and signal-to-noise, does not meet observational requirements. To address these problems, a new race-track type probe is designed based on a magnetic core made of a Co-based amorphous ribbon. The size of this single-component probe is only Φ10 mm × 30 mm. The signal processing circuit is also optimized. The whole size of the sensor integrated with probes and data acquisition module is Φ70 mm × 100 mm. Compared with traditional fluxgate and micro-fluxgate sensors, the designed sensor is compact and provides excellent performance equal to traditional fluxgate sensors with good linearity and RMS noise of less than 0.1 nT. From operational tests, the results are in good agreement with those from a standard fluxgate magnetometer. Being more suitable for modern dense deployment of geomagnetic observations, this small-size fluxgate sensor offers promising research applications at lower costs.
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Siradjuddin, Indrazno, Rendi Pambudi Wicaksono, Anggit Murdani, Denda Dewatama, Ferdian Ronilaya, Erfan Rohadi, and Rosa Andrie Asmara. "A low cost 3D-printed robot joint torque sensor." MATEC Web of Conferences 197 (2018): 11006. http://dx.doi.org/10.1051/matecconf/201819711006.
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Technological advances allow researchers to develop advanced arm robots and can safely work side by side with humans Therefore, a robot arm controller can be designed in such way that the robot arm can move along the desired trajectories and act upon external influences, in this last case, the torque sensor plays an important rule. Currently torque sensors are available in the market has a high price. In this work, an inexpensive robot joint torque sensor is presented. Most parts of this sensor are made using 3D printers. While the other components are easily can be found in the market and with a relatively low-costs. The development of this sensor is intended to facilitate the prototyping of the robot arm for educational and research purposes. The basic idea of the sensor mechanism is to convert torque into a force absorbed by a spring. Then, the encoder senses the direction and the value of the input torque. This torque sensor can be easily too customized. Thus this sensor can be tailored to the needs by replacing some parts such as encoder and spring. The mechanism of this sensor can also be adjusted with the actuator to be paired. Experiments have been conducted to verify the accuracy and the performance of the proposed torque sensor.
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Cannon, M. E., R. Nayak, G. Lachapelle, O. S. Salychev, and V. V. Voronov. "Low-Cost INS/GPS Integration: Concepts and Testing." Journal of Navigation 54, no. 1 (January 2001): 119–34. http://dx.doi.org/10.1017/s0373463300001259.
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The high cost of inertial units is the main obstacle for their inclusion in precision navigation systems to support a variety of application areas. Standard inertial navigation systems (INS) use precise gyro and accelerometer sensors; however, newer inertial devices with compact, lower precision sensors have become available in recent years. This group of instruments, called motion sensors, is six to eight times less costly than a standard INS. Given their weak stand-alone accuracy and poor run-to-run stability, such devices are not usable as sole navigation systems. Even the integration of a motion sensor into a navigation system as a supporting device requires the development of non-traditional approaches and algorithms. The objective of this paper is to assess the feasibility of using a motion sensor, specifically the MotionPak™, integrated with DGPS and DGLONASS information, to provide accurate position and attitude information, and to assess its capability to bridge satellite outages for up to 20 seconds. The motion sensor has three orthogonally mounted ‘solid-state’ micro- machined quartz angular rate sensors, and three high performance linear servo accelerometers mounted in a compact, rugged package. Advanced algorithms are used to integrate the GPS and motion sensor data. These include INS error damping, calculated platform corrections using DGPS (or DGPS/DGLONASS) output, velocity correction, attitude correction and error model estimation for prediction. This multi-loop algorithm structure is very robust, which guarantees a high level of software reliability. Vehicular and aircraft test trials were conducted with the system in land vehicle mode and the results are discussed. Simulated outages in GPS availability were made to assess the bridging accuracy of the system. Results show that a bridging accuracy of up to 3 m after 10 seconds in vehicular mode and a corresponding accuracy of 6 m after 20 seconds in aircraft mode can be obtained, depending on vehicle dynamics and the specific MotionPak™ unit used. The attitude accuracy was on the order of 22 to 25 arcmin for roll and pitch, and about 44 arcmin for heading.
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Watkins, A. Neal, Brett R. Wenner, Jeffrey D. Jordan, Wenying Xu, James N. Demas, and Frank V. Bright. "Portable, Low-Cost, Solid-State Luminescence-Based O2 Sensor." Applied Spectroscopy 52, no. 5 (May 1998): 750–54. http://dx.doi.org/10.1366/0003702981944175.
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A novel sensor for quantifying molecular O2 based entirely on solid-state electronics is presented. The sensor is based on the luminescence quenching of tris(4,7-diphenyl-1, 10-phenanthroline)ruthenium(II) ([Ru(dpp)3]2+) by molecular O2. The sensor involves immobilizing the ruthenium complex within a porous sol-gel-processed glass film and casting this film directly onto the surface of a blue quantum-well light-emitting diode (LED). The ruthenium complex is excited by the LED, the [Ru(dpp)3]2+ emission is filtered from the excitation with a low-cost acrylic color filter, and the emission is detected with an inexpensive silicon photodiode. The sensor response to gaseous O2 and dissolved O2 in water is presented. The sensor exhibits fast response times and good reversibility, and detection limits are 0.5%, 0.02%, and 110 ppb, respectively, for O2 in the gaseous (linear Stern–Vobner and multi-site Stern–Volmer analysis) and aqueous phase. This sensor provides a cost-effective alternative to traditional electrochemical-based O2 sensing and also provides a platform for other optically based sensors.
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Badura, Marek, Piotr Batog, Anetta Drzeniecka-Osiadacz, and Piotr Modzel. "Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring." Journal of Sensors 2018 (October 31, 2018): 1–16. http://dx.doi.org/10.1155/2018/5096540.
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Low-cost sensors are an opportunity to improve the spatial and temporal resolution of particulate matter data. However, such sensors should be calibrated under conditions close to the final ones before any monitoring actions. The paper presents the results of a collocated comparison of four models of low-cost optical sensors with a TEOM 1400a analyser. SDS011 (Nova Fitness), ZH03A (Winsen), PMS7003 (Plantower), and OPC-N2 (Alphasense) sensors were used in this research. Three copies of each sensor model were placed in a common box to compare the sensor performance under the same measurement conditions. Monitoring of the PM2.5 fraction was conducted for almost half a year from 21 August 2017 to 19 February 2018 in Wrocław (Poland). Reproducibility between sensor units was assessed on the basis of coefficient of variation (CV). CV values were lower than 7% in the case of SDS011 and PMS7003 sensors and equal to 20% for OPC-N2 units. CV was higher than 50% for ZH03A, mainly due to malfunctions. During the measurements, the trends of outputs from sensors were generally similar to TEOM data, but significant overestimation of PM2.5 concentrations was observed for the sensor raw data. A high linear relationship between TEOM and sensors was noticed for 1 min, 15 min, and 1-hour averaged data for PMS7003 sensors (R2≈0.83–0.89), for SDS011 units (R2≈0.79–0.86), and for one unit of ZH03A (R2≈0.74–0.81). R2 values for daily averages were at the level 0.91–0.93 for PMS7003, 0.87–0.90 for SDS011, and 0.89 for ZH03A. OPC-N2 had only a moderate linear relationship with TEOM (R2≈0.53–0.69 for daily data and 0.43–0.61 for shorter time averages). Quite large dispersion of data and high relative errors of PM2.5 estimation were observed for concentration ranges below 20–30 μg/m3. The impact of high relative humidity level was observed for SDS011 and OPC-N2 devices—clear overestimation of outputs was observed above 80% RH.
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Smith, Katie R., Peter M. Edwards, Mathew J. Evans, James D. Lee, Marvin D. Shaw, Freya Squires, Shona Wilde, and Alastair C. Lewis. "Clustering approaches to improve the performance of low cost air pollution sensors." Faraday Discussions 200 (2017): 621–37. http://dx.doi.org/10.1039/c7fd00020k.
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Low cost air pollution sensors have substantial potential for atmospheric research and for the applied control of pollution in the urban environment, including more localized warnings to the public. The current generation of single-chemical gas sensors experience degrees of interference from other co-pollutants and have sensitivity to environmental factors such as temperature, wind speed and supply voltage. There are uncertainties introduced also because of sensor-to-sensor response variability, although this is less well reported. The sensitivity of Metal Oxide Sensors (MOS) to volatile organic compounds (VOCs) changed with relative humidity (RH) by up to a factor of five over the range of 19–90% RH and with an uncertainty in the correction of a factor of two at any given RH. The short-term (second to minute) stabilities of MOS and electrochemical CO sensor responses were reasonable. During more extended use, inter-sensor quantitative comparability was degraded due to unpredictable variability in individual sensor responses (to either measurand or interference or both) drifting over timescales of several hours to days. For timescales longer than a week identical sensors showed slow, often downwards, drifts in their responses which diverged across six CO sensors by up to 30% after two weeks. The measurement derived from the median sensor within clusters of 6, 8 and up to 21 sensors was evaluated against individual sensor performance and external reference values. The clustered approach maintained the cost competitiveness of a sensor device, but the median concentration from the ensemble of sensor signals largely eliminated the randomised hour-to-day response drift seen in individual sensors and excluded the effects of small numbers of poorly performing sensors that drifted significantly over longer time periods. The results demonstrate that for individual sensors to be optimally comparable to one another, and to reference instruments, they would likely require frequent calibration. The use of a cluster median value eliminates unpredictable medium term response changes, and other longer term outlier behaviours, extending the likely period needed between calibration and making a linear interpolation between calibrations more appropriate. Through the use of sensor clusters rather than individual sensors, existing low cost technologies could deliver significantly improved quality of observations.
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Fries, David, Stanislav Ivanov, Pragnesh Bhanushali, James Wilson, Heather Broadbent, and Arthur Sanderson. "Broadband, Low-Cost, Coastal Sensor Nets." Oceanography 20, no. 4 (December 1, 2007): 150–55. http://dx.doi.org/10.5670/oceanog.2007.15.
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Kaplan, Ben-Zion, Vladimir Boroda, and Uri Suissa. "Low-cost DC electric field sensor." Sensors and Actuators A: Physical 134, no. 2 (March 2007): 396–98. http://dx.doi.org/10.1016/j.sna.2006.06.009.
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Sydenham, P. H., V. Taing, D. J. Mounsey, and Yu Wen-Xin. "Low-cost, precision, flat inductive sensor." Measurement 15, no. 3 (June 1995): 179–88. http://dx.doi.org/10.1016/0263-2241(94)00048-c.
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Bertetto, A. Manuello, and M. Ruggiu. "Low cost resistive based touch sensor." Mechanics Research Communications 30, no. 2 (March 2003): 101–7. http://dx.doi.org/10.1016/s0093-6413(02)00362-2.
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Kawadiya, Siddharth, Claire Welling, Sonia Grego, and Marc A. Deshusses. "Fecal Malodor Detection Using Low-Cost Electrochemical Sensors." Sensors 20, no. 10 (May 20, 2020): 2888. http://dx.doi.org/10.3390/s20102888.
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Technology innovation in sanitation is needed for the 4.2 billion people worldwide, lacking safely managed sanitation services. A major requirement for the adoption of these technologies is the management of malodor around toilet and treatment systems. There is an unmet need for a low-cost instrumented technology for detecting the onset of sanitation malodor and triggering corrective actions. This study combines sensory data with low-cost gas sensor data on malodor emanating from feces. The response of 10 commercial electrochemical gas sensors was collected alongside olfactometric measurements. Odor from fecal specimens at different relevant dilution as well as specimens with pleasant odors as a control were evaluated for a total of 64 responses. Several of the sensors responded positively to the fecal odor, with the formaldehyde, hydrogen sulfide, and ammonia sensors featuring the highest signal to noise ratio. A positive trend was observed between the sensors’ responses and the concentration of the odorant and with odor intensity, but no clear correspondence with dilution to threshold (D/T) values was found. Selected sensors were responsive both above and below the intensity values used as the cutoff for offensive odor, suggesting the possibility of using those sensors to differentiate odor offensiveness based just on the magnitude of their response. The specificity of the sensors suggested that discrimination between the selected non-fecal and fecal odors was possible. This study demonstrates that some of the evaluated sensors could be used to assemble a low-cost malodor warning system.
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Lehtola, V. V., H. Hyyti, and T. Malkamäki. "WHY IT MAKES SENSE TO USE HIGH COST SENSORS TO DO LOW COST SENSOR RESEARCH." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W1-2022 (December 8, 2022): 137–43. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w1-2022-137-2022.
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Abstract. The question is highly topical in the world that is aiming to acclaim more efficiency through an omnipresence of sensors. The implication of the omnipresence of sensors clearly is that most of these sensors will be of the low-cost type. Hence, there is a call for research utilizing low-cost sensors. However, paradoxically, it often makes sense to use high-cost sensors to do this research. Here, we open up this apparent paradox and argue why high-cost sensors are not only greatly useful but also critically required in low-cost sensor research. We offer different examples that support this argument but discuss also limitations and cases where the argument does not hold.
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Rahman, Mahbubur, Dali Ismail, Venkata P. Modekurthy, and Abusayeed Saifullah. "LPWAN in the TV White Spaces." ACM Transactions on Embedded Computing Systems 20, no. 4 (June 2021): 1–26. http://dx.doi.org/10.1145/3447877.
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Low-Power Wide-Area Network (LPWAN) is an enabling Internet-of-Things technology that supports long-range, low-power, and low-cost connectivity to numerous devices. To avoid the crowd in the limited ISM band (where most LPWANs operate) and cost of licensed band, the recently proposed Sensor Network over White Spaces (SNOW) is a promising LPWAN platform that operates over the TV white spaces. As it is a very recent technology and is still in its infancy, the current SNOW implementation uses the Universal Software Radio Peripheral devices as LPWAN nodes, which has high costs (≈$750 USD per device) and large form-factors, hindering its applicability in practical deployment. In this article, we implement SNOW using low-cost, low form-factor, low-power, and widely available commercial off-the-shelf (COTS) devices to enable its practical and large-scale deployment. Our choice of the COTS device (TI CC13x0: CC1310 or CC1350) consequently brings down the cost and form-factor of a SNOW node by 25× and 10×, respectively. Such implementation of SNOW on the CC13x0 devices, however, faces a number of challenges to enable link reliability and communication range. Our implementation addresses these challenges by handling peak-to-average power ratio problem, channel state information estimation, carrier frequency offset estimation, and near-far power problem. Our deployment in the city of Detroit, Michigan, demonstrates that CC13x0-based SNOW can achieve uplink and downlink throughputs of 11.2 and 4.8 kbps per node, respectively, over a distance of 1 km. Also, the overall throughput in the uplink increases linearly with the increase in the number of SNOW nodes.
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Samad, Abdul, Freddy Ernesto Melchor Mimiaga, Bernd Laquai, and Ulrich Vogt. "Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air Quality." Sensors 21, no. 3 (January 26, 2021): 804. http://dx.doi.org/10.3390/s21030804.
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Air pollution in urban areas is a huge concern that demands an efficient air quality control to ensure health quality standards. The hotspots can be located by increasing spatial distribution of ambient air quality monitoring for which the low-cost sensors can be used. However, it is well-known that many factors influence their results. For low-cost Particulate Matter (PM) sensors, high relative humidity can have a significant impact on data quality. In order to eliminate or reduce the impact of high relative humidity on the results obtained from low-cost PM sensors, a low-cost dryer was developed and its effectiveness was investigated. For this purpose, a test chamber was designed, and low-cost PM sensors as well as professional reference devices were installed. A vaporizer regulated the humid conditions in the test chamber. The low-cost dryer heated the sample air with a manually adjustable intensity depending on the voltage. Different voltages were tested to find the optimum one with least energy consumption and maximum drying efficiency. The low-cost PM sensors with and without the low-cost dryer were compared. The experimental results verified that using the low-cost dryer reduced the influence of relative humidity on the low-cost PM sensor results.
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Komarizadehasl, Seyedmilad, Behnam Mobaraki, Haiying Ma, Jose-Antonio Lozano-Galant, and Jose Turmo. "Low-Cost Sensors Accuracy Study and Enhancement Strategy." Applied Sciences 12, no. 6 (March 21, 2022): 3186. http://dx.doi.org/10.3390/app12063186.
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Today, low-cost sensors in various civil engineering sectors are gaining the attention of researchers due to their reduced production cost and their applicability to multiple nodes. Low-cost sensors also have the advantage of easily connecting to low-cost microcontrollers such as Arduino. A low-cost, reliable acquisition system based on Arduino technology can further reduce the price of data acquisition and monitoring, which can make long-term monitoring possible. This paper introduces a wireless Internet-based low-cost data acquisition system consisting of Raspberry Pi and several Arduinos as signal conditioners. This study investigates the beneficial impact of similar sensor combinations, aiming to improve the overall accuracy of several sensors with an unknown accuracy range. The paper then describes an experiment that gives valuable information about the standard deviation, distribution functions, and error level of various individual low-cost sensors under different environmental circumstances. Unfortunately, these data are usually missing and sometimes assumed in numerical studies targeting the development of structural system identification methods. A measuring device consisting of a total of 75 contactless ranging sensors connected to two microcontrollers (Arduinos) was designed to study the similar sensor combination theory and present the standard deviation and distribution functions. The 75 sensors include: 25 units of HC-SR04 (analog), 25 units of VL53L0X, and 25 units of VL53L1X (digital).
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Jaywant, Swapna A., Harshpreet Singh, and Khalid Mahmood Arif. "Low-Cost Sensor for Continuous Measurement of Brix in Liquids." Sensors 22, no. 23 (November 25, 2022): 9169. http://dx.doi.org/10.3390/s22239169.
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This paper presents a Brix sensor based on the differential pressure measurement principle. Two piezoresistive silicon pressure sensors were applied to measure the specific gravity of the liquid, which was used to calculate the Brix level. The pressure sensors were mounted inside custom-built water-tight housings connected together by fixed length metallic tubes containing the power and signal cables. Two designs of the sensor were prepared; one for the basic laboratory testing and validation of the proposed system and the other for a fermentation experiment. For lab tests, a sugar solution with different Brix levels was used and readings from the proposed sensor were compared with a commercially available hydrometer called Tilt. During the fermentation experiments, fermentation was carried out in a 1000 L tank over 7 days and data was recorded and analysed. In the lab experiments, a good linear relationship between the sugar content and the corresponding Brix levels was observed. In the fermentation experiment, the sensor performed as expected but some problems such as residue build up were encountered. Overall, the proposed sensing solution carries a great potential for continuous monitoring of the Brix level in liquids. Due to the usage of low-cost pressure sensors and the interface electronics, the cost of the system is considered suitable for large scale deployment at wineries or juice processing industries.
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Dean, Robert N. "A Frequency Swept Low-Cost Capacitive Fringing Field PCB Sensor." International Symposium on Microelectronics 2017, no. 1 (October 1, 2017): 000157–62. http://dx.doi.org/10.4071/isom-2017-tp56_043.
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Abstract Reliable, low-cost sensors are important for many applications, including agriculture, pollution monitoring and weather forecasting. Commercial printed circuit board technology is being used to develop simple sensors for these applications, where the resistance or capacitance of the sensor is measured at a single frequency to determine useful information about an environmental parameter of interest. However, by measuring the complex impedance of the sensor over a wide frequency range, additional useful information can be obtained about the sensing environment. As a proof of principle, a suitable sensor was developed and evaluated in various aqueous solutions of interest using this technique. The measured sensor impedance was reduced to a capacitance versus frequency plot and a resistance versus frequency plot. Different aqueous solution chemistries resulted in characteristic signatures on these plots that could be useful in identifying the chemical compositions of the various solutions. Di-ionized water was used as a reference for chemical comparison. Various aqueous solution chemistries were then compared with DI water, resulting in corresponding signature differences of 10% to 50%.
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Sun, Yi, Amirhosein Mousavi, Shahir Masri, and Jun Wu. "Socioeconomic Disparities of Low-Cost Air Quality Sensors in California, 2017–2020." American Journal of Public Health 112, no. 3 (March 2022): 434–42. http://dx.doi.org/10.2105/ajph.2021.306603.
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Objectives. To (1) examine the disparity in availability of PurpleAir low-cost air quality sensors in California based on neighborhood socioeconomic status (SES) and exposure to fine particulate matter smaller than 2.5 micrometers (PM2.5), (2) investigate the temporal trend of sensor distribution and operation, and (3) identify priority communities for future sensor distribution. Methods. We obtained census tract–level SES variables and PM2.5 concentrations from the CalEnviroScreen4.0 data set. We obtained real-time PurpleAir sensor data (July 2017–September 2020) to examine sensor distribution and operation. We conducted spatial and temporal analyses at the census tract level to investigate neighborhood SES and PM2.5 concentrations in relation to sensor distribution and operation. Results. The spatial coverage and the number of PurpleAir sensors increased significantly in California. Fewer sensors were distributed in census tracts with lower SES, higher PM2.5, and higher proportions of racial/ethnic minority populations. Furthermore, a large proportion of existing sensors were not in operation at a given time, especially in disadvantaged communities. Conclusions. Disadvantaged communities should be given access to low-cost sensors to fill in spatial gaps of air quality monitoring and address environmental justice concerns. Sensor purchasing and deployment must be paired with regular maintenance to ensure their reliable performance. (Am J Public Health. 2022;112(3):434–442. https://doi.org/10.2105/AJPH.2021.306603 )
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Zhang, Yichao, Lakitha O. H. Wijeratne, Shawhin Talebi, and David J. Lary. "Machine Learning for Light Sensor Calibration." Sensors 21, no. 18 (September 18, 2021): 6259. http://dx.doi.org/10.3390/s21186259.
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Sunlight incident on the Earth’s atmosphere is essential for life, and it is the driving force of a host of photo-chemical and environmental processes, such as the radiative heating of the atmosphere. We report the description and application of a physical methodology relative to how an ensemble of very low-cost sensors (with a total cost of <$20, less than 0.5% of the cost of the reference sensor) can be used to provide wavelength resolved irradiance spectra with a resolution of 1 nm between 360–780 nm by calibrating against a reference sensor using machine learning. These low-cost sensor ensembles are calibrated using machine learning and can effectively reproduce the observations made by an NIST calibrated reference instrument (Konica Minolta CL-500A with a cost of around USD 6000). The correlation coefficient between the reference sensor and the calibrated low-cost sensor ensemble has been optimized to have R2> 0.99. Both the circuits used and the code have been made publicly available. By accurately calibrating the low-cost sensors, we are able to distribute a large number of low-cost sensors in a neighborhood scale area. It provides unprecedented spatial and temporal insights into the micro-scale variability of the wavelength resolved irradiance, which is relevant for air quality, environmental and agronomy applications.
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Lee, Hoochang, Jiseock Kang, Sungjung Kim, Yunseok Im, Seungsung Yoo, and Dongjun Lee. "Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor." Sensors 20, no. 13 (June 27, 2020): 3617. http://dx.doi.org/10.3390/s20133617.
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Low-cost light scattering particulate matter (PM) sensors have been widely researched and deployed in order to overcome the limitations of low spatio-temporal resolution of government-operated beta attenuation monitor (BAM). However, the accuracy of low-cost sensors has been questioned, thus impeding their wide adoption in practice. To evaluate the accuracy of low-cost PM sensors in the field, a multi-sensor platform has been developed and co-located with BAM in Dongjak-gu, Seoul, Korea from 15 January 2019 to 4 September 2019. In this paper, a sample variation of low-cost sensors has been analyzed while using three commercial low-cost PM sensors. Influences on PM sensor by environmental conditions, such as humidity, temperature, and ambient light, have also been described. Based on this information, we developed a novel combined calibration algorithm, which selectively applies multiple calibration models and statistically reduces residuals, while using a prebuilt parameter lookup table where each cell records statistical parameters of each calibration model at current input parameters. As our proposed framework significantly improves the accuracy of the low-cost PM sensors (e.g., RMSE: 23.94 → 4.70 μ g/m 3 ) and increases the correlation (e.g., R 2 : 0.41 → 0.89), this calibration model can be transferred to all sensor nodes through the sensor network.
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MAHORE, AMAN, H. L. KUSHWAHA, ADARSH KUMAR, and TAPANK KHURA. "A low-cost wheel slip measurement device for agricultural tractors." Indian Journal of Agricultural Sciences 92, no. 3 (March 29, 2022): 334–38. http://dx.doi.org/10.56093/ijas.v92i3.122681.
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Tractor wheel slip affects the traction of a tractor, fuel efficiency and tyres adversely, along with compaction of the soil. Tractor operators cannot sense the slip unless it continues for some significant time. In the present study, a low-cost slip measuring device and an indicator were developed at ICAR-IARI, New Delhi (2018) and installed on the tractor dashboard for the operator’s information. It warns the operator about slip both by visual and auditory signals to adjust the driving accordingly. In this study, four different sensors (Inductive proximity sensor, IR sensor, Hall effect sensor, and Photo-electric sensor) were tested for measurement of rotational speed under different working conditions of light and dust. Hall effect sensor was found the best for all the operational conditions. So, a low-cost slip measuring device was developed with the Hall effect sensor integrated with a microcontroller as a retrofit for tractors. The device was mounted on the tractor, and field experiments were conducted. The results obtained from the developed device showed that the values were statistically close to actual values.
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Wu, Xiang, and Fang Ming Deng. "A Capacitive Humidity Sensor for Low-Cost Low-Power Application." Applied Mechanics and Materials 556-562 (May 2014): 1847–51. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.1847.
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This paper presents a capacitive humidity sensor in CMOS technology. The humidity sensor element is implemented in standard CMOS technology without any further post-processing, which results in low fabrication cost. The sensor interface employs a fully-digital architecture based on phase locked loop, which results in low pow dissipation. The proposed humidity sensor is fabricated in TSMC 0.18μm CMOS process and the chip occupies an area of 0.05mm2. The measurement result shows that the sensor value exhibits good linearity within the range of 10-90%RH and the interface circuit consumes only 1.05μW at 0.5V supply voltage.
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Yuting Li, Yuting Li, Wentao Zhang Wentao Zhang, Zhaogang Wang Zhaogang Wang, Hongbin Xu Hongbin Xu, Jing Han Jing Han, and Fang Li Fang Li. "Low-cost and miniature all-silica Fabry–Perot pressure sensor for intracranial pressure measurement." Chinese Optics Letters 12, no. 11 (2014): 111401–4. http://dx.doi.org/10.3788/col201412.111401.
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Cherqui, F., R. James, P. Poelsma, M. J. Burns, C. Szota, T. Fletcher, and J. L. Bertrand-Krajewski. "A platform and protocol to standardise the test and selection low-cost sensors for water level monitoring." H2Open Journal 3, no. 1 (January 1, 2020): 437–56. http://dx.doi.org/10.2166/h2oj.2020.050.
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Abstract Water infrastructure in cities is complex and requires proactive management to optimise function. The scale and distribution of assets across municipalities requires affordable systems which can trigger alerts. Systems underpinned by low-cost sensors could meet increasing monitoring needs: more assets, more often, and at a better resolution. However, low-cost sensors require appropriate testing to assess their performance and optimise their use. Here, we focus on low-cost water level sensors, often considered as the main monitoring parameters for water-related infrastructures. We developed a platform and testing protocol to assess the suitability of low-cost sensors. We assessed the performance of three widely used low-cost sensors: laser-ranging, ultrasonic-ranging, and pressure. Our main results showed that the ultrasonic sensor offers the best price to accuracy ratio, and the pressure sensor provides the highest accuracy while still at a very low cost. Our platform and protocol provide a standardised testing and calibration method which can be applied to any sensor. The platform can be used to gather and share results, to enhance community knowledge and encourage the use of new (low-cost or not) sensors. The development of low-cost sensors is an important step toward the wider use monitoring systems for water infrastructure.
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Canu, Michaël, Boris Gálvis, and Malika Madelin. "What does the Shinyei PPD42NS Low-Cost Dust Sensor Really Measure?" International Journal of Environmental Science and Development 12, no. 1 (2021): 1–9. http://dx.doi.org/10.18178/ijesd.2021.12.1.1310.
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Deteriorating air quality is of great concern around the world. Recently, citizen scientists, researchers, and many others have used low-cost devices such as the Shinyei PPD42NS dust sensor to measure particulate matter pollution in both developed and under-developed countries. However, few articles exist specifically on the features and performance of these sensors. Some have shown mixed results in terms of precision, accuracy, and repeatability, especially for portable applications. Frequently, users assemble the electronics and the sensors applying simple guidelines, using electric schematics, and coding extraneous algorithms to get questionable data. There is a need to better understand how it works exactly, its limitations and the effect of the program used to interpret the outputs of this sensor. This article provides a short electronic analysis of the Shinyei PPD42NS dust sensor and shows that the internal sensor electronic design (filters and detection stage) as well as the used data processing algorithm, limit its precision and accuracy by generating nonlinearities and biases. These issues avoid some applications like moving ones and imply that the algorithm used to process the sensor signals must be clearly presented in future articles.
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Beisteiner, Christoph, and Bernhard G. Zagar. "A survey of inkjet-printed low-cost sensors." tm - Technisches Messen 85, no. 7-8 (July 26, 2018): 504–14. http://dx.doi.org/10.1515/teme-2017-0136.
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Abstract Inkjet-printers from the company Epson and others can be used to fabricate low-cost sensors on coated PET films. By using nanoparticle-based dispersions resistive temperature dependent sensors, strain gauges, thermocouples and pressure sensors can be fabricated. For these purposes the gauge factors, Seebeck coefficients and temperature coefficients of resistance for Ag, Carbon Black and PEDOT:PSS dispersions on Mitsubishi® and Pelikan® PET substrates are characterized. Furthermore, piezoresistive effects in transverse and longitudinal strain directions are discussed. Additionally, a printed sensor system for measuring strains within a surface is presented. Finally, an injection-moulding process and a lamination process are used to improve the mechanical scratching of those sensors.
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deSouza, Priyanka Nadia. "Key Concerns and Drivers of Low-Cost Air Quality Sensor Use." Sustainability 14, no. 1 (January 5, 2022): 584. http://dx.doi.org/10.3390/su14010584.
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Low-cost sensors are revolutionizing air pollution monitoring by providing real-time, highly localized air quality information. The relatively low-cost nature of these devices has made them accessible to the broader public. Although there have been several fitness-of-purpose appraisals of the various sensors on the market, little is known about what drives sensor usage and how the public interpret the data from their sensors. This article attempts to answer these questions by analyzing the key themes discussed in the user reviews of low-cost sensors on Amazon. The themes and use cases identified have the potential to spur interventions to support communities of sensor users and inform the development of actionable data-visualization strategies with the measurements from such instruments, as well as drive appropriate ‘fitness-of-purpose’ appraisals of such devices.
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Andel, Ján, Vojtech Šimák, Alžbeta Kanálikova, and Rastislav Pirník. "GNSS Based Low-Cost Magnetometer Calibration." Sensors 22, no. 21 (November 3, 2022): 8447. http://dx.doi.org/10.3390/s22218447.
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With the development of MEMS sensors, the magnetometer has increasingly become a part of various wearable devices. The magnetometer measures the intensity of the magnetic field in all three axes, resulting in a 3D vector—direction and power. Calibration must be done before using a magnetometer, especially in wearable electronics, due to the low quality of the sensor and high proximity to other electromagnetic emission sources. Several magnetometer calibration algorithms exist in the literature, with most of them requiring multi-sided rotation. However, such calibration is highly impractical when the sensor is mounted on larger objects, e.g., vehicles, which cannot easily be rotated. Vehicles contain a large amount of ferromagnetic soft and hard material that affects the measured magnetic field. A magnetometer can be useful for an INS system in a car as long as it does not drift over time. This article describes how to calibrate a magnetometer using the GNSS motion vector. The calibration is performed using data from the initial section of the vehicle’s trajectory. The quality of the calibration is then validated using the remaining section of the trajectory, comparing the deviation between the azimuth obtained by GNSS and by the calibrated magnetometer. Based on the azimuth and speed of the vehicle, we predicted the position of the vehicle and plotted the prediction on the map. The experiment showed that such calibration is functional. The uncalibrated data were unusable due to the strong effect of ferromagnetic soft and hard materials in the vehicle.
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Wang, Xian Wei, and Jun Hai Jiang. "A Low-Cost MEMS Implementation Based on Sensor Fusion Algorithms." Applied Mechanics and Materials 738-739 (March 2015): 42–45. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.42.
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In this paper a low-cost Micro-Electro-Mechanical System (MEMS) inertial measurement unit is designed, a 3-axis accelerometer and 3-axis gyroscope simulated 6 degrees of freedom orientation sensing through sensor fusion. By analyzing a simple complimentary filter and a more complex Kalman filter, the outputs of each sensor were combined and took advantage of the benefits of both sensors to improved results. The experimental results demonstrate that the output signal can be corrected suitability by means of the proposed method.
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Day, Rong-Fuh, Peng-Yeng Yin, Yuh-Chin T. Huang, Cheng-Yi Wang, Chih-Chun Tsai, and Cheng-Hsien Yu. "Concentration-Temporal Multilevel Calibration of Low-Cost PM2.5 Sensors." Sustainability 14, no. 16 (August 12, 2022): 10015. http://dx.doi.org/10.3390/su141610015.
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Ambient aerosols have a significant impact on plant species mortality, air pollution, and climate change. It is critical to monitor the concentrations of aerosols, especially particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM2.5), which has a direct relationship with human respiratory diseases. Recently, low-cost PM2.5 sensors have been deployed to provide a denser monitoring coverage than that of government-built monitoring supersites, which only give a macro perspective of air quality. To increase the measurement accuracy, low-cost sensors need to be calibrated. In current practice, regression techniques are used to calibrate sensors. This paper proposes a concentration-temporal multilevel calibration method to cope with the varying regression relation in different concentration and temporal domains. The performance of our method is evaluated with real field data from a supersite sensor and a low-cost sensor deployed in Puli, Taiwan. The experimental results show that our calibration method significantly outperforms linear regression in terms of R2, Root Mean Square Error, and Normalized Mean Error. Moreover, our method compares favorably with a machine learning calibration method based on gradient regression tree boosting.
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Concas, Francesco, Julien Mineraud, Eemil Lagerspetz, Samu Varjonen, Xiaoli Liu, Kai Puolamäki, Petteri Nurmi, and Sasu Tarkoma. "Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration." ACM Transactions on Sensor Networks 17, no. 2 (June 2021): 1–44. http://dx.doi.org/10.1145/3446005.
Full textAbstract:
The significance of air pollution and the problems associated with it are fueling deployments of air quality monitoring stations worldwide. The most common approach for air quality monitoring is to rely on environmental monitoring stations, which unfortunately are very expensive both to acquire and to maintain. Hence, environmental monitoring stations are typically sparsely deployed, resulting in limited spatial resolution for measurements. Recently, low-cost air quality sensors have emerged as an alternative that can improve the granularity of monitoring. The use of low-cost air quality sensors, however, presents several challenges: They suffer from cross-sensitivities between different ambient pollutants; they can be affected by external factors, such as traffic, weather changes, and human behavior; and their accuracy degrades over time. Periodic re-calibration can improve the accuracy of low-cost sensors, particularly with machine-learning-based calibration, which has shown great promise due to its capability to calibrate sensors in-field. In this article, we survey the rapidly growing research landscape of low-cost sensor technologies for air quality monitoring and their calibration using machine learning techniques. We also identify open research challenges and present directions for future research.