Proximity Sensors Research Articles

Using Mobile and Fixed Internet of Things Sensing Networks, Real-Time Monitoring and Prediction of Air Quality in One\'s Immediate Vicinity

Abstract: A significant global problem has emerged in several locations as a result of air pollution and its adverse impact on human well-being. Recently, there has been a rise in the number of researchers that are keen on evaluating and forecasting the air quality in close proximity to individuals. The use of the Internet of Things (IoT) across several businesses has significantly enhanced people's quality of life by interconnecting multiple sensors in diverse locations. Moreover, the Internet of Things (IoT) has streamlined the task of monitoring air pollution. The conventional utilization of stationary sensors is inadequate for acquiring an accurate and all-encompassing representation of the air pollution levels in close proximity to people. This is due to the fact that the sensors in closest proximity to people may be located many kilometers apart from each other. The objective of our study is to construct a model that precisely depicts the air quality pattern within a certain geographic area. This objective will be accomplished by using a combination of stationary and portable Internet of Things sensors. The sensors are affixed to vehicles that are carrying out surveillance in the vicinity. Our methodology allows for a thorough examination of the whole spectrum of air quality fluctuations in neighboring regions. Through the use of many machine learning algorithms and realworld data, we showcase the efficacy of our methodology in accurately discerning and forecasting air quality without compromising on accuracy. The results of our research indicate that there is significant potential for efficiently monitoring and forecasting air quality in the context of a smart city.

Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing

Wheat, being the third largest U.S. crop and the principal food grain, faces significant risks from climate extremes such as drought. This necessitates identifying and developing methods for early water-stress detection to prevent yield loss and improve water-use efficiency. This study investigates the potential of hyperspectral imaging to detect the early stages of drought stress in wheat. The goal is to utilize this technology as a tool for screening and selecting drought-tolerant wheat genotypes in breeding programs. Additionally, this research aims to systematically evaluate the effectiveness of various existing sensors and methods for detecting early stages of water stress. The experiment was conducted in a durum wheat experimental field trial in Maricopa, Arizona, in the spring of 2019 and included well-watered and water-limited treatments of a panel of 224 replicated durum wheat genotypes. Spectral indices derived from hyperspectral imagery were compared against other plant-level indicators of water stress such as Photosystem II (PSII) and relative water content (RWC) data derived from proximal sensors. Our findings showed a 12% drop in photosynthetic activity in the most affected genotypes when compared to the least affected. The Leaf Water Vegetation Index 1 (LWVI1) highlighted differences between drought-resistant and drought-susceptible genotypes. Drought-resistant genotypes retained 43.36% more water in leaves under well-watered conditions compared to water-limited conditions, while drought-susceptible genotypes retained only 15.69% more. The LWVI1 and LWVI2 indices, aligned with the RWC measurements, revealed a strong inverse correlation in the susceptible genotypes, underscoring their heightened sensitivity to water stress in earlier stages. Several genotypes previously classified based on their drought resistance showed spectral indices deviating from expectations. Results from this research can aid farmers in improving crop yields by informing early management practices. Moreover, this research offers wheat breeders insights into the selection of drought-tolerant genotypes, a requirement that is becoming increasingly important as weather patterns continue to change.

Automatic Tube Counter Monitoring System using Infrared Sensor based on NODEMCU ESP8266

Technology is needed in every industry because it can simplify the production process, improve production quality, and enhance the company's reputation in the sight of consumers. The cylinder counting activity at PT Batuah Energi Indonesia is still done manually, involving time and standardized estimation of LPG cylinder loads, which faces inaccuracy issues. In fact, PT Batuah Energi Indonesia has facilities that handle many LPG cylinders from various users and providers of LPG cylinders. While accurate cylinder counts are beneficial to the industry, companies need technology that can automatically calculate the number of filled LPG cylinders. Therefore, this study was carried out to demonstrate to students how to develop automatic tube counters using an infrared E18-D80NK as a tube detector, NodeMCU microcontrollers ESP8266 as controllers, Arduino IDE for developing programs, and IoT for remote monitoring. The developed device approach, specifically using the E18-D80NK infrared proximity sensor based on the NodeMCU ESP8266, can be coded using the Arduino IDE compiler. For the detection of the number of tubes, the E18-EN80K infrared sensor is used and data transmission wirelessly utilizes the Blynk application. The results of the automatic tube counter monitoring tool were successfully tested with a 100% accuracy rate, utilizing the E18-D80NK infrared sensor and NodeMCU microcontroller ESP8266, and can be monitored remotely using Blynk.

Design and Implementation Proximity Based IoT for Smart Attendance System

The reporting of course attendance is an essential component of academic administration. This research designs and deploys a smart attendance system by leveraging proximity-based IoT. The smart attendance system is built upon the Android operating system to detect the beacon of the proximity sensor and is integrated into a database installed on a cloud server. The application supports three different features designated for administrators, lecturers, and students, respectively. The developed application accelerates data input for the campus administrator, records the course log efficiently, and concurrently reports the more secure student attendance from manipulation since it applies a single user identity. This study conducts a field test to evaluate the operational efficacy of the system by sampling students who enrolled in the course. The test involves utilizing a range of mobile devices to access the application connected to two courses. In one course, the functionality testing result is 91.67%, while in another, it is 100% successful. The limitation arises as a result of the incapability of the mobile device to perceive the beacon.

AUTOMATIC PNEUMATIC BUMPER FOR FOUR-WHEELER

The technology of pneumatics has gained tremendous importance in the field of workplace rationalization and automation from old-fashioned timber works and coal mines to modern machine shops and space robots. It is therefore important that technicians and engineers should have a good knowledge of pneumatic system, air operated valves and accessories. The aim is to design and develop a control system based an intelligent electronically controlled automotive bumper activation system is called “AUTOMATIC PNEUMATIC BUMPER”. This system is consisting of IR transmitter and Receiver circuit, Control Unit, Pneumatic bumper system. The IR sensor is used to detect the obstacle. There is any obstacle closer to the vehicle (within 4 feet), the control signal is given to the bumper activation system. The pneumatic bumper system is used to product the man and vehicle. This bumper activation system is only activated the vehicle speed above 40-50 km per hour. This vehicle speed is sensed by the proximity sensor and this signal is given to the control unit and pneumatic bumper activation system. Key Words: IR transmitter and Receiver circuit, Control Unit, Pneumatic bumper system, Flow control valve, Solenoid Valve, Pneumatic single acting cylinder.

Test Control of Inclusive Physical Education: Assessment Using the Newest Electronics

The purpose of the study was to determine the effectiveness of a device developed based on the latest electronics to control the coordination of movements of the lower limbs of students with disabilities. Materials and methods. 34 students with disabilities were involved in the study. At the time of the experiment, they had functional disorders of the lower limbs as a result of injuries and received a doctor’s permission to participate in the experiment. The research was conducted at the theoretical and empirical levels, using the following methods: analysis, synthesis, systematization, generalization, technical modeling, pedagogical testing, and mathematical statistics. Results. In the research process, a device was used, which was developed as part of the conducted research. The device consists of two rubber mats in which capacitive proximity sensors are placed. The test task involves recording the number of touches of rubber mats in 20 seconds. The information received from the sensors during the student’s performance of the test task, namely the alternate touching of the rubber mat with the big toe, is sent to the microcontroller via an infrared communication line. The development uses a high-performance microcontroller ATMega 328P, which can support a wide range of sensors and generate information about the time and frequency of leg movements. The signals of the student’s toes touching the rubber mats, received by capacitive sensors, are processed by a microcontroller and displayed on a PC through a serial connection and using the Arduino software, which allows reading the received information about the execution of movements. Under the conditions of the pedagogical experiment, we tried to determine the quality of the measurement results. According to the obtained numerical indicators, the numerical values of the test authenticity obtained by the traditional method of fixing the results by a specialist correspond to the value “low”. The results of the validity calculations showed that the correlation between the test measurement results and the evaluation results using the developed device was optimal with a correlation coefficient greater than 0.6. Conclusions. The importance of a high level of development of the coordination of movements of the lower limbs of students with disabilities is determined by the need to develop this quality to ensure the effectiveness of their rehabilitation in the process of inclusive PE. The analysis of the obtained material allows us to state that the practical application of the inclusive PE device developed based on the latest electronics will allow scientifically based optimization of this process to ensure its effectiveness.

Wireless Charging of Electric Vehicle While Moving with dual input Sources

This project presents a novel localization method for electric vehicles (EVs) charging through wireless power transmission (WPT) and solar based charging. With the proposed technique, the wireless charging system can self-determine the most efficient coil to transmit power at the EV’s position based on the proximity sensors activated by its wheels. To ensure optimal charging, our approach involves measurement of the transfer efficiency of individual transmission coil to determine the most efficient one to be used. This not only improves the charging performance, but also minimizes energy losses by autonomously activating only the coils with the highest transfer efficiencies. The results show that with the proposed system it is possible to detect the coil with maximum transmitting efficiency without the use of actual power transmission and comparison of the measured efficiency. This project also proves that with the proposed charger set-up, the position of the receiver coil can be detected almost instantly and get charge while moving in the road. This indeed saves energy and boosts the charging time. Here we also introduce the solar panel in the top of the EV which indeed saves energy and boosts the charging time in day time. The vehicle battery voltage and current data can be monitoring continuously and updated in online.

Stretchable ionic composites for strain-insensitive dual-mode pressure and proximity sensors

Simultaneously sensing pressure and proximity allows for the detection of contact pressure and the distance of approaching objects. This dual functionality ensures precise human–machine interactions and real-time adaptive responses to dynamic environments, proving it useful in human–machine interfaces, robots, and wearable devices. In this study, we introduce a highly stretchable and strain-insensitive pressure and proximity sensor capable of maintaining its electrical properties under mechanical deformations, achieved by establishing a continuous conductive pathway through an ionic bridge between conductive fillers. The strain-insensitive and stretchable composite exhibits ΔR/R0 of 0.024 under stretching up to 140% after 1,000 times. When the strain-insensitive composite is combined with a micro-patterned insulating layer, the resulting piezoresistive pressure sensors exhibit uniform pressure sensing capability even under mechanical deformations of tensile strain (∼50%) and bending curvature (1.3 cm−1). Moreover, our pressure sensor can be functioned as a capacitive-type proximity sensor capable of identifying material, shape, and distance of approaching objects with high sensitivity (capacitance change (ΔC/C0) of −0.88). As a proof-of-concept demonstration, our dual-mode pressure sensor with a multichannel array enables real-time monitoring of contact/noncontact pressure distribution, including intensity, shape, and proximity regardless of mechanical interference and surface roughness. Our approach to achieving high sensitivity and selectivity for desired contact/noncontact stimuli independent of mechanical interferences offers a novel platform for practical sensor applications.

Life cycle assessment of four different precision agriculture technologies and comparison with a conventional scheme

Precision farming technologies have the potential to enhance agricultural sustainability, but their exact environmental impact remains uncertain. This study aimed to (1) compare the life cycle assessment (LCA) of a conventional five-year crop rotation system with and without precision agriculture technologies (PATs) in Lower Austria; (2) to assess the emission hotspots and (3) to perform a sensitivity analysis on fertilization using the DeNitrification-DeComposition (DNDC) soil model to quantifying soil emission. Evaluated PATs included automatic steering systems, automatic section control (ASC), proximal sensors, and prescription maps from remote sensors. The crop rotation system included spring barley, soy, winter wheat, rapeseed, and winter barley. Assessed agricultural processes encompassed tillage, seeding, plant protection, fertilization, and harvesting. The impacts evaluated were climate change, fine particulate matter formation, freshwater eutrophication, freshwater ecotoxicity, terrestrial acidification, terrestrial ecotoxicity, and human carcinogenic toxicity. The sensor scheme scenario showed the highest reductions in climate change, followed by the prescription map, ASC, and autosteer scheme with reductions of −17.0, −8.9, −6.4, and −2.4%, respectively. This study emphasizes the potential of PATs to minimize environmental impacts in crop production while recognizing the influence of site and technology-specific factors. Future research should consider local variables for a comprehensive environmental assessment.

Synergistic use of proximally sensed and time series remotely sensed imagery to map soil sodicity

Soil sodicity can cause crusting in the topsoil which impedes water infiltration, and erosion in the subsoil owing to instability. These can impose constraints to sugarcane growth in the form of reduced plant emergence and root extension. To improve soil capability, a map of topsoil (0–0.15 m) exchangeable sodium percentage (ESP) can be used to determine the amount of gypsum required to ameliorate soil condition. Herein, a digital soil mapping (DSM) approach was used to map top- and subsoil (0.3–0.45 m) ESP. To do this, we first examined prediction agreement of a calibration model between digital data and ESP, first comparing individual use of remotely sensed time series imagery (i.e., Sentinel-2 and Landsat-8) or proximal sensor (i.e., electromagnetic [EM] induction and gamma-ray [γ-ray]) data. To account for the large amount of remote data we combined them using principal component analysis (PCA). We also investigated combining digital data using a backward feature elimination – BFE), along with minimum calibration sample size (n = 150–10) determined. Prediction agreement (Lin's concordance correlation coefficient – LCCC) and accuracy (ratio of performance to deviation – RPD) were assessed using an independent validation dataset (n = 32). To predict topsoil ESP, PCs from Landsat-8 provided excellent (LCCC = 0.90) agreement and very good (RPD = 2.26) accuracy, followed by Sentintel-2 (0.86, 1.75), γ-ray (0.83, 1.84) and EM (0.78, 1.78), with subsoil ESP also excellent (0.90) and very good (2.51) using Landsat-8, however; Sentintel-2 outperformed the others with even better results (0.95, 3.24), followed by EM (0.78, 1.76) and γ-ray (0.73, 1.54). Moreover, slightly better results were achieved when EM, γ-ray, and PCs of Sentinel-2 were combined, with top- and subsoil ESP agreement (0.93 and 0.94, respectively) and accuracy (2.53 and 3.14, respectively) excellent. A minimum of 40 sampling sites were required (1.2 sites ha−1) for the good prediction agreement and accuracy of top- (0.85, 2.13) and subsoil (0.84, 1.90) ESP. Based on the best results, DSM of ESP was made to recommend gypsum application rates to ameliorate sodic soils according to the Six-Easy-Steps Management Guidelines. The northern fields required variable rates (5, 7.5, and 10 t ha−1) of gypsum, whereas the southern fields would not require gypsum.

IMPLEMENTASI SISTEM PENGENDALI WASTAFEL CUCI TANGAN BERBASIS IoT MENGGUNAKAN PLATFORM BLNYK

The enhancement of cleanliness and sanitation has become a paramount concern in modern society, particularly in the face of a global pandemic. In this context, this research proposes and implements an Internet of Things (IoT)-based handwashing sink control system using the BLNYK platform, ESP8266 module, infrared proximity sensor E-18-DNK, solenoid valve DC 12V, and LM259 stepdown. The system is designed to provide an efficient and hygienic handwashing experience. The ESP8266 module serves as the central brain connected to the BLNYK platform, enabling users to remotely access and control the sink via mobile devices or computers. The infrared proximity sensor E-18-DNK detects the presence of user hands, triggering the solenoid valve DC 12V to automatically dispense water. Additionally, the LM259 stepdown is utilized to regulate voltage and optimize power consumption, making the system energy-efficient. Sink usage data and usage statistics can be accessed through the BLNYK platform, facilitating efficient monitoring and analysis. Test results demonstrate the system's reliability in accurately detecting hands and providing a swift response in opening the solenoid valve. Furthermore, the implementation of the LM259 stepdown successfully optimizes the power consumption of the system, making it an energy-efficient solution. Thus, this system can serve as a model for further development in creating IoT-based intelligent solutions to enhance cleanliness and sanitation in various environments, including households, public spaces, and healthcare facilities.

From screen to soft power: the rising appeal of Turkish TV series in Bangladesh

Abstract Purpose This study examines the popularity of Turkish TV series in Bangladesh and their effectiveness as a soft power tool for Turkey. It also aims to understand why these series have been successful in shaping the attitudes and beliefs of Bangladeshi audiences towards Turkey and its leadership. Method This qualitative study employs the narrative analysis approach to examine the phenomenon. Social media posts and comments related to the Bengali dubbed version of the Turkish TV series The Magnificent Century on Facebook and YouTube from November 2015 to March 2022 were collected and analyzed using an inductive approach. Findings The study finds that the success of Turkish TV series in Bangladesh can be attributed to a combination of factors, including the absence of quality local content, the strong connection of Bangladeshi audiences with their Muslim identity, and the portrayal of Islamic historical context and similar Muslim culture. The positive image of Turkey and its history portrayed in these series has created a sense of cultural proximity between Turkey and Bangladesh, contributing to the popularity of Turkish TV series in the country. Implications The study suggests that Turkish TV series serve as a soft power tool for Turkey to increase its influence in Bangladesh. By promoting a positive image of Turkey and its history, these series have successfully shaped the attitudes and beliefs of Bangladeshi audiences towards Turkey and its leadership. Value This study highlights the effectiveness of Turkish TV series as a soft power tool. It provides insights into the factors contributing to the popularity of these series in Bangladesh and their potential to increase Turkey’s influence in the Muslim world.

Bioinspired ion channel receptor based on hygroelectricity for precontact sensing of living organism

Tactile sensors play an important role in human-machine interaction (HMI). Compared to contact tactile sensing, which leaves physical hardware vulnerable to wear and tear, proximity sensing is better at reacting to remote events before physical contact. The apteronotus albifrons possess ion channel receptors for remote surroundings perception. Inspired by the relevant ion channel structure and self-powered operation mode, we designed a new proximity sensor with ion rectification characteristics and self-powered capability. This bio-inspired ion channel receptor exploits the hygroelectric effect to convert the humidity information into a series of current signals when the living organism approaches, and it is insensitive to non-aquatic non-organisms. The sensor offers high sensitivity (2.3 mm−1), a suitable range (0–10 mm) for close object detection, fast response (0.3 s), and fast recovery (2.5 s). The unique combination of bio-sensitivity, non-contact detection characteristics, and humidity-based power generation capabilities enriches the functionality of future HMI electronics. As a proof of concept, the sensor has been successfully applied in different scenarios such as human health management, early warning systems, non-contact switches to prevent virus transmission, object recognition, and finger trajectory detection.

Rancang Bangun Pengembangan Sistem Pompa Galon Air Otomatis Dengan Sensor Infrared Untuk Efisiensi Penggunaan Air Minum

This study examines the automation of electric gallon pumps for drinking water. This automation involves replacing the manual button on the gallon pump with a sensor, which turns on the pump and dispenses drinking water when the glass gets closer without pressing the button. This tool can also be used for gallons of drinking water ranging in size from 5 liters, 10 liters, to 15 liters. The system is designed for practical applications, and all its components are tested to understand their respective functions so as to understand the type of module that suits their needs. Test results reveal that the system is functioning as intended. Electric pump modules, infrared proximity sensors, and relay modules are some of its components.

Priority RPL for IOT Based Smart Manufacturing Industries

A routing protocol used in heterogeneous transport networks for low-power, lossy networks. This is a routing protocol for wireless networks. This protocol follows the same specifications as Zigbee, 6 lopan is IEEE 802.15. 4 Enables both many-to-one and one-to-one communication. To address the need for enhancing in this study proposes a novel methodology called RPL-PG (Routing Protocol for Low-Power and Lossy Networks Priority Generation). Initially sensors like Temperature, Humidity, Vibration, Proximity, Gas and Current Monitoring Sensors are used for smart manufacturing. Consequently, Destination Oriented Directed Acyclic Graph (DODAG) is used for RPL configuration. Based on selected RPL configuration the priority is generated using assign priority count and priority-based queuing. Finally, Fuzzy rules are used to select the RPL path and then update the DODAG finally reached the destination. The study involves setting up a simulated environment using appropriate tools, such as MATLAB. Experimental findings evaluate and compares performance measures, such as Energy Consumption, Network Life Time, Packet Loss Ratio, Packet Delivery Ratio (PDR), E2E Delay, and Network Throughput. The Energy Consumption of the proposed RPL-PG method achieves 43.6 % lower than 38 % and 35.8 % in terms of OMC-RPL and RMA-RP respectively.

Remote Sensing and Kriging with External Drift to Improve Sparse Proximal Soil Sensing Data and Define Management Zones in Precision Agriculture

The precision agriculture scientific field employs increasingly innovative techniques to optimize inputs, maximize profitability, and reduce environmental impacts. Therefore, obtaining a high number of soil samples to make precision agriculture feasible is challenging. This data bottleneck has been overcome by identifying sub-regions based on data obtained through proximal soil sensing equipment. These data can be combined with freely available remote sensing data to create more accurate maps of soil properties. Furthermore, these maps can be optimally aggregated and interpreted for soil heterogeneity through management zones. Thus, this work aimed to create and combine soil management zones from proximal soil sensing and remote sensing data. To this end, data on electrical conductivity and magnetic susceptibility, both apparent, were measured using the EM38-MK2 proximal soil sensor and the contents of the thorium and uranium elements, both equivalent, via the Medusa MS1200 proximal soil sensor for a 72-ha grain-producing area in São Paulo, Brazil. The proximal soil sensing attributes were mapped using ordinary kriging (OK). Maps were also made using kriging with external drift (KED), and the proximal soil sensor attributes data, combined with remote sensing data, such as Landsat-8, Aster, and Sentinel-2 images, in addition to 10 terrain covariables derived from the digital elevation model Alos Palsar. As a result, three management zone maps were produced via the k-means clustering algorithm: using data from proximal sensors (OK), proximal sensors combined with remote sensors (KED), and remote sensors. Seventy-two samples (0–10 cm in depth) were collected and analyzed in a laboratory (1 sample per hectare) for concentrations of clay, calcium, organic carbon, and magnesium to assess the capacity of the management zone maps created using analysis of variance. All zones created using the three data groups could distinguish the different treatment areas. The three data sources used to map management zones produced similar map zones, but the zone map using a combination of proximal and remote data did not show an improvement in defining the management zones, and using only remote sensing data lowered the significance levels of differentiating each zone compared to the OK and KED maps. In summary, this study not only underscores the global applicability of proximal and remote sensing techniques in precision agriculture but also sheds light on the nuances of their integration. The study’s findings affirm the efficacy of these advanced technologies in addressing the challenges posed by soil heterogeneity, paving the way for more nuanced and site-specific agricultural practices worldwide.

Connecting Internet of Drones and Urban Computing: Methods, protocols and applications

This comprehensive survey explores the connection between the Internet of Drones (IoD) and Urban Computing (UC). Drones offer substantial benefits across diverse urban applications encompassing public safety, transportation management, delivery services, and emergency response, among others. To ensure the seamless operation of these applications, efficient airspace management is imperative. Consequently, an essential foundation is to establish a communication infrastructure coupled with an accompanying supportive system that caters to drones, control bases, service providers, and the Internet. Termed the IoD, this framework facilitates drones’ control management, synchronization, coordination and monitoring of drones to attain their objectives effectively. Moreover, IoD applications are poised to propel societal advancement by aligning with the goals of UC. UC is an interdisciplinary domain to enhances human well-being by harnessing data from various sources, including the Global Positioning System (GPS), cameras, proximity sensors, and social networks. This survey thoroughly examines and analyzes multifaceted aspects underpinning how the IoD can significantly benefit UC. It encompasses applications, their requisites, design protocols specific to IoD, and the challenges inherent within this evolving realm. To the best of our knowledge, our work is one of the first studies to directly relate and show how the IoD can contribute to all UC-applications categories.

Detecting cool-climate Riesling vineyard variation using unmanned aerial vehicles and proximal sensors

The ability to detect and respond to vineyard spatial variation can lead to improved management—a practice known as precision viticulture. The goal of this study was to determine if remote sensors can enhance precision viticulture applications by detecting vineyard spatial variation. The hypothesis was that differences in vine spectral reflectance, as detected by remote sensors, would be associated with variations in viticultural variables due to known relationships with vine size, structure, and pigmentation. Riesling grapevines were geolocated within six commercial vineyards across Niagara, Ontario. Water status, vine size, winter hardiness, virus titer, yield components, and berry composition were measured on these vines. Remote sensing technologies subsequently collected multispectral data by unmanned aerial vehicles and by proximal sensing technology (GreenSeeker™), which were transformed into the Normalized Difference Vegetation Index (NDVI). Direct relationships between NDVI and vine size, water status, yield, berry weight, and titratable acidity were observed, as well as inverse relationships between NDVI and Brix and potentially volatile terpenes. Remote sensing demonstrated the ability to detect vineyard areas differing in measures of vine health, yield, and berry composition in certain sites and years; however, more research is needed to determine when these technologies should be used for precision viticulture applications.

Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior during a predation event: A case study from Scandinavia.

Although the advent of high-resolution GPS tracking technology has helped increase our understanding of individual and multispecies behavior in wildlife systems, detecting and recording direct interactions between free-ranging animals remains difficult. In 2023, we deployed GPS collars equipped with proximity sensors (GPS proximity collars) on brown bears (Ursus arctos) and moose (Alces alces) as part of a multispecies interaction study in central Sweden. On 6 June, 2023, a collar on an adult female moose and a collar on an adult male bear triggered each other's UHF signal and started collecting fine-scale GPS positioning data. The moose collar collected positions every 2 min for 89 min, and the bear collar collected positions every 1 min for 41 min. On 8 June, field personnel visited the site and found a female neonate moose carcass with clear indications of bear bite marks on the head and neck. During the predation event, the bear remained at the carcass while the moose moved back and forth, moving toward the carcass site about five times. The moose was observed via drone with two calves on 24 May and with only one remaining calf on 9 June. This case study describes, to the best of our knowledge, the first instance of a predation event between two free ranging, wild species recorded by GPS proximity collars. Both collars successfully triggered and switched to finer-scaled GPS fix rates when the individuals were in close proximity, producing detailed movement data for both predator and prey during and after a predation event. We suggest that, combined with standard field methodology, GPS proximity collars placed on free-ranging animals offer the ability for researchers to observe direct interactions between multiple individuals and species in the wild without the need for direct visual observation.

Autonomous and smart cleaning mobile robot system to improve the maintenance efficiency of solar photovoltaic array

A solar photovoltaic (PV) array is part of a PV power plant as a generation unit. PV array that are usually placed on top of buildings or the ground will be very susceptible to dirt and dust. Thus, this dirt and dust will be able to reduce the performance and work efficiency of the generation unit. Cleaning PV arrays by manpower requires high effort, cost, and risk, especially in higher location. This study presents the design of a mobile robot that is used to replace human labor to clean PV arrays. That way, the PV array maintenance steps can reduce operational costs and risks. This intelligent controlled mobile robot can maneuver safely and efficiently over PV arrays. gyroscope and proximity sensors are used to detect and follow the sweep path over the entire PV array area. Proportional integral derivative (PID) control test makes the robot can stabilize in about 5.72 seconds to keep on the track. The smart PV cleaning robot has average operation time about 13 minutes in autonomous mode and 20-24 minutes in manual mode. The operation of the robot is effective to give more efficiency on the use of energy, time, and maintenance costs of PV array system.