This article presents the implementation of a self-hosted Internet of Things solution on a personal computer. The proposed solution utilizes open-source software components to create a low-cost and customizable altern...
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Wireless sensor networks (WSNs) are pivotal in diverse applications, from environmental monitoring to industrial automation. Securing these networks is crucial, and clock synchronization stands out as a critical chall...
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ISBN:
(数字)9798350371567
ISBN:
(纸本)9798350371574
Wireless sensor networks (WSNs) are pivotal in diverse applications, from environmental monitoring to industrial automation. Securing these networks is crucial, and clock synchronization stands out as a critical challenge. The Kalman filter, known for its efficacy in state estimation and noise reduction, addresses clock synchronization vulnerabilities in WSNs. By modeling clock synchronization as a dynamic system, the Kalman filter adapts to estimate clock drifts, compensating for network conditions and security threats. It offers real-time adjustment of synchronization parameters, effectively mitigating threats like malicious biasing and timing attacks. The Dual Kalman Filter is an essential addition to this approach. Operating two Kalman filters simultaneously, it enhances clock synchronization by compensating for diverse sources of clock deviation across the network. This dual filtering approach improves accuracy and resilience against irregularities, contributing significantly to WSN reliability and security. In tandem, Long Short-Term Memory (LSTM) networks are integral to WSNs, addressing temporal data analysis and enhancing prediction, monitoring, and decision- making. LSTM models detect anomalies, ensuring WSN integrity by recognizing unexpected sensor behavior and securing data transmissions. Integrating LSTM into WSN applications enhances their capabilities while considering resource constraints inherent in wireless sensor environments.
Due to the difficulty and significance of the Internet of Things (IoT), the highest standards of data protection are essential to the successful growth of any smart city or technical endeavour that relies on the IoT. ...
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This work presents temperature display on web browser using Ethernet Shield And LM 35 sensor based on Arduino IDE Environment. The web page programming was realized with Arduino Mega 2560 microcontroller using C/C++ l...
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Wireless sensor Networks (WSNs) are of great importance in various military and civilian applications, such as data collection and area monitoring. WSNs have many active research areas, including energy consumption, r...
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ISBN:
(数字)9798331533557
ISBN:
(纸本)9798331533564
Wireless sensor Networks (WSNs) are of great importance in various military and civilian applications, such as data collection and area monitoring. WSNs have many active research areas, including energy consumption, routing protocols, node deployment, localization, and security, making it a rich topic for research. However, node deployment still faces significant challenges, such as coverage ratio, connectivity, and overlapping sensor ranges. This paper presents a novel approach to optimizing node placement in WSNs using a modified Particle Swarm Optimization (mPSO) algorithm. Our method addresses the issues of coverage holes and overlapping sensor ranges. Initially, sensor nodes are randomly deployed within the region of interest (ROI). The mPSO algorithm iteratively refines the node positions to maximize area coverage while minimizing overlap, identifying gaps in the ROI and covering them with the nearest mobile node. This optimization process enhances sensor network coverage by over 35% compared to random deployment, improving overall performance and extending network lifetime.
This study evaluates the accuracy of three different types of time-of-flight sensors to measure distance. We envision the possible use of these sensors to localize swarms of flying light specks (FLSs) to illuminate ob...
This study evaluates the accuracy of three different types of time-of-flight sensors to measure distance. We envision the possible use of these sensors to localize swarms of flying light specks (FLSs) to illuminate objects and avatars of a metaverse. An FLS is a miniature-sized drone configured with RGB light sources. It is unable to illuminate a point cloud by itself. However, the inter-Flsrelationship effect of an organizational framework will compensate for the simplicity of each individual FLS, enabling a swarm of cooperating FLSs to illuminate complex shapes and render haptic interactions. Distance between FLSs is an important criterion of the inter-FLS relationship. We consider sensors that use radio frequency (UWB), infrared light (IR), and sound (ultrasonic) to quantify this metric. Obtained results show only one sensor is able to measure distances as small as 1 cm with a high accuracy. A sensor may require a calibration process that impacts its accuracy in measuring distance.
A highly sensitive, facial, low-cost, eco-friendly and flexible Interdigital electrode (IDE) humidity sensor for field and medical application is presented in this work. The sensor is designed from copper tap as elect...
A highly sensitive, facial, low-cost, eco-friendly and flexible Interdigital electrode (IDE) humidity sensor for field and medical application is presented in this work. The sensor is designed from copper tap as electrodes with a non-woven paper both as a sensing layer and substrate material. The response of sensor is observed for the percentage relative humidity (%RH) ranging from 30-100% is from 50pF-944pF, having fast response time of ~1.2s and recovery time of ~1.75s with sensitivity of 14.75pF/%RH. The sensor stability and repeatability response is also observed by testing it for different temperature values. The fabricated sensor is efficient in term of response, sensitivity, and stability which makes it promising candidates for medical and field applications.
Contactless vital sign monitoring systems are becoming increasing in demand for a wide range of biomedical applications. Millimetre-wave radars and embedded signal processing are the most promising technologies to ena...
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ISBN:
(数字)9781728127828
ISBN:
(纸本)9781728127828
Contactless vital sign monitoring systems are becoming increasing in demand for a wide range of biomedical applications. Millimetre-wave radars and embedded signal processing are the most promising technologies to enable non-contact vital signs monitoring. In this work, the challenging task of heart rate estimation from radar data has been addressed. Three different radar systems from Infineon, Texas Instruments and Acconeer, and four algorithms, FFT, Median-FFT, STFT and Median-STFT, have been analysed and compared against a reference sensor. Accuracy, as well as power figures, have been reported for all the radar systems. A dataset of 16 volunteers has been acquired, yielding a total of 400 minutes of radar-recorded vital sign data. The accuracy of the four investigated algorithms has been reported on average and per subject for every radar. The algorithm exploiting the Short Time Fourier Transform (STFT) is able to achieve an error as low as 0.02% on a single person and of 6.4% in heart rate estimation on average across the whole dataset.
Image and video processing is a major contributor of object’s detection, since only video sensor can analyze a lot of visual information specific of road scene. Notably road signs identification in images. Which is a...
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New trends and advancements in communication and sensing technologies in Precision Farming (PF) offer opportunities to farmers for a continuous and real-time monitoring applications, which are mainly based on the use ...
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ISBN:
(纸本)9781665414937
New trends and advancements in communication and sensing technologies in Precision Farming (PF) offer opportunities to farmers for a continuous and real-time monitoring applications, which are mainly based on the use of Wireless sensor Networks (WSNs). Animal monitoring and supervision is one critical aspect in PF, where various types of sensing and control systems are employed. However, available solutions for animal monitoring portrait a compromise between performance and system efficiency in terms of energy consumption, memory allocation, hardware size, and cost. In this work, an energy-efficient, lightweight, and cost effective wireless sensor node for animal monitoring is designed. The designed system is compact and small in size with a dimension of 26 x 33 mm. During its active state, the current consumption of the designed sensor node using ADXL is in the range from 3 to 9 mA at a sampling frequency of 12 Hz.
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