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Advanced Flood Management and Rescue Strategies to Securing Lives from Flood Risks

Advanced Flood Management and Rescue Strategies to Securing ...

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International conference on ent Computing and Control Systems (ICICCS)

作者： Manoranjitham E Kavin V Prasand S Praveen Kumar B Saravanan R Department of Electronics and Telecommunication Karpagam College of Engineering Coimbatore Tamilnadu India

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

Both the locating of flood victims and the provision of continuous alarm information to the Disaster Rescue Force are accomplished by the Flood alarm and Rescue System. Additionally, it shows where the individuals who are trapped in the water are. Afterwards, a flood alarm system might be activated to notify the public. Contrarily, in an emergency, the Rescue System will direct the rescue workers to the people who need them. The individuals in need will activate the rescue operation by pressing the button that the government has given them. The "rescue team will use the signal processing device to receive and decode the encoded communication signal that it emits". Because of this, they will be able to find the individual far more quickly than was previously achievable with the technology at their disposal. This is the case since the top goals of the rescuing force are determined by our system. Our prototype is built with the idea that individuals may simply incorporate the gadget into their daily tasks when floods are in the area. The inclusion of a torch in our product ensures its continued viability and makes it suitable for usage in low-light situations, such as during floods.

关键词： Temperature sensors Wireless sensor networks Force Prototypes Pressing Signal processing Control systems Real-time systems Floods Testing

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Self-Organized sensor Eggs for Decentralized Localization and Sensing on Vulcano Island – A Glimpse into Future Space Exploration with Swarms

Self-Organized Sensor Eggs for Decentralized Localization an...

引用

International conference on information Fusion

作者： Fabio Broghammer Thomas Wiedemann Siwei Zhang Armin Dammann Christian Gentner Petar Djuric Institute of Communications and Navigation German Aerospace Center (DLR) Germany Perception for Intelligent Systems Munich Institute of Robotics and Machine Intelligence TU Munich Germany Department of Electrical and Computer Engineering Stony Brook University USA

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

Robotic swarms or portable sensor networks are emerging technologies for sensing physical processes that are spatially distributed- and temporally dynamic, both on Earth and in future Moon/Mars exploration missions. We develop a portable network composed of a multitude of self-organized “sensor eggs”. These eggs are equipped with ultra-wideband (UWB) transceivers, providing precise time and position information without additional infrastructures like Global Navigation Satellite Systems (GNSSs). Each egg is additionally equipped with environmental sensors, for example, a Sulfur dioxide gas sensor to explore volcanic activity. We use a real time decentralized particle filter (DPF) to estimate the a-posteriori probability density functions (PDFs) of the egg positions. These PDFs are then used in a static state binary Bayes filter for estimating the gas sources with potentially complex structures such as cracks on the volcano surface. The proposed sensor network is verified with an in-field experiment at La Fossa volcano on the island of Vulcano, Italy, in 2023.

关键词： Location awareness Volcanic activity Probability density function Robot sensing systems Particle filters Transceivers sensors Timing Surface cracks Ultra wideband technology

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A Wireless sensor Network-Based Testbed for Characterizing the Dispersion of Total Volatile Organic Compounds in an Enclosed Space

A Wireless Sensor Network-Based Testbed for Characterizing t...

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Omni-layer intelligent Systems (COINS), International conference on

作者： Neil Astrologo Ren Paulo Estaquio Sarah Montecillo Heinrich Gasacao Aldon Cris Galido John Jairus Eslit Percival Magpantay Marc Rosales Julius Rhoan Lustro Joseph Gerard Reyes John Richard Hizon UP Center for Air Research in Urban Environments Quezon City Philippines

ISBN: (数字)9798350349597

ISBN: (纸本)9798350349603

An indoor air quality monitoring system can provide information about the air quality in enclosed spaces such as offices, and potentially prevent occupants from suffering illnesses due to staying in enclosed spaces, more commonly known as Sick Building Syndrome (SBS). Experiments were conducted to characterize the spread of Total Volatile Organic Compounds (TVOC) in a room, using ESP32-based sensor nodes were equipped with SGP30 and CCS811 TVOC sensors. This setup was used as a testbed to monitor pollutant concentrations at different points in 3D space. Discrepancies in the measurements between points showed that airflow has a large effect in reducing pollutant concentrations.

关键词： Volatile organic compounds Wireless communication Wireless sensor networks Three-dimensional displays Buildings Pollution measurement intelligent systems

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Elements of TinyML on Constrained Resource Hardware 6th

Elements of TinyML on Constrained Resource Hardware

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6th International conference on Advances in Computing and Data Sciences (ICACDS)

作者： Tsoukas, Vasileios Gkogkidis, Anargyros Kakarountas, Athanasios Univ Thessaly Intelligent Syst Lab Dept Comp Sci & Biomed Informat Lamia Greece

ISBN: (纸本)9783031126413;9783031126406

The next phase of intelligent computing could be entirely reliant on the Internet of Things (IoT). The IoT is critical in changing industries into smarter entities capable of providing high-quality services and products. The widespread adoption of IoT devices raises numerous issues concerning the privacy and security of data gathered and retained by these services. This concern increases exponentially when such data is generated by healthcare applications. To develop genuinely intelligent devices, data must be transferred to the cloud for processing due to the computationally costly nature of current Neural Network implementations. Tiny Machine Learning (TinyML) is a new technology that has been presented by the scientific community as a means of developing autonomous and secure devices that can gather, process, and provide output without transferring data to remote third party organizations. This work presents three distinct TinyML applications to cope with the aforementioned issues and open the road for intelligent machines that provide tailored results to their users.

关键词： Internet of Things TinyML Neural networks Constrained hardware Emerging technologies

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Research on multi-node gait information acquisition system and time synchronization based on BLE

Research on multi-node gait information acquisition system a...

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Robotics, intelligent Control and Artificial Intelligence (RICAI), International conference on

作者： Yuqi Gao Chao Yu Xu Zhou Junjie Liu Zhiming Yao Ning Lin Institute of Intelligent Machines Hefei Institutes of Physical Science Chinese Academy of Sciences University of Science and Technology of China Hefei China Chinese Academy of Sciences Hefei Institutes of Physical Science Hefei China Department of Neurosurgery The First People's Hospital of Chuzhou The Affliated Chuzhou Hospital of Anhui Medical University Chuzhou China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

Gait information is critical in various domains. However, achieving accurate time synchronization across multiple sensor nodes in wireless systems remains a challenge, particularly in gait information acquisition, where precise data alignment is essential. Current solutions are limited by high power consumption, system complexity, and transmission instability. This study proposes a multi-node gait information acquisition system incorporating a six-axis inertial sensor and a plantar pressure sensor, with the ESP32 serving as the core processing unit. The system utilizes the low-power Bluetooth protocol for real-time data transmission. To address the issue of time desynchronization, we introduce an average error-based time synchronization algorithm. The algorithm was tested in an experimental setup using a signal generator, two gait systems, and a mobile device. The results demonstrate that the average error method effectively estimates and corrects frequency drift, significantly reducing time synchronization errors. The system offers a low-power, high-precision solution for multi-node gait information acquisition, advancing the accuracy of gait data fusion and analysis.

关键词： Pressure sensors Time-frequency analysis Power demand Inertial sensors Signal generators Mobile handsets Frequency estimation Synchronization Data communication Frequency synchronization

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Research and Development of Wireless sensor Network Detection Software

Research and Development of Wireless Sensor Network Detectio...

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Signal processing and intelligent Computing (SPIC), International conference on

作者： Yue Zhou Siming Huang Hong Wang Xiaotong Zhou Shenyang Ligong University Shenyang China New South Wales University Sydney Australia

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

This paper investigates the technology of sensor network node parameter monitoring software and designs a complete monitoring software solution in conjunction with a specific application scenario of greenhouse monitoring. The communication data verification algorithm is thoroughly studied in this study, and the discussion and research on the nonlinear calibration algorithm of sensor parameters in data processing are conducted. The CRC cyclic redundancy algorithm and the least squares method are employed in the subsequent software design for relevant data *** real-time monitoring system is based on sensor network technology, integrating measurement and control to achieve remote monitoring. The system formats the data and uploads it to the host computer via COM serial communication according to the set transmission mode and communication protocol. Upon receiving a series of data packets, the system analyzes the data, dynamically displays it in real-time, issues normal or alarm messages, and notifies the system through different means. The software of this system demonstrates good operational performance, meeting the basic requirements of the application scenario. It possesses excellent monitoring real-time capability, openness, and compatibility, providing comprehensive information and decision support for sensor network node parameter monitoring.

关键词： Wireless sensor networks Software design Software algorithms Signal processing algorithms Termination of employment Software Real-time systems Calibration Software measurement Monitoring

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Channel-Aware Direct Localization Using One-Bit Quantized Measurements

Channel-Aware Direct Localization Using One-Bit Quantized Me...

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European Signal processing conference (EUSIPCO)

作者： Guoxin Zhang Yunfei Liang Wei Yi Hien Quoc Ngo Michail Matthaiou Pramod K. Varshney School of Information and Communication Engineering University of Electronic Science and Technology of China P. R. China Centre for Wireless Innovation (CWI) Queen's University Belfast U.K Department of Electrical Engineering and Computer Science Syracuse University USA

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

To address the constraints of limited transmission bandwidth and power consumption in wireless sensor networks (WSNs), this paper proposes a direct localization method using one-bit quantized measurements. Specifically, the received signal is quantized into its one bit version at the local sensor before being transmitted to the fusion center (FC) for target localization. Recognizing the imperfections of the wireless channel between the sensors and the FC, a channel-aware position estimator using one-bit quantized measurements is proposed. Furthermore, the Cramér-Rao lower bound (CRLB) of the proposed channel-aware estimator is also derived to theoretically assess the localization performance. Simulation results demonstrate that the proposed channel-aware position estimator approaches its theoretical performance bounds and is superior compared to that of the channel-unaware estimator.

关键词： Location awareness Wireless communication Wireless sensor networks Quantization (signal) Power measurement Power demand Simulation Channel estimation Robustness sensors

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AoI-aware DAV Data Collection Based on the IRS's Phase Estimation in Wireless sensor networks

AoI-aware DAV Data Collection Based on the IRS's Phase Estim...

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International conference on Wireless Communications and Signal processing (WCSP)

作者： Jiaqi Tang Juan Liu Xiaofan He Lingfu Xie Long Qu School of Electrical Engineering and Computer Science Ningbo University Zhejiang China Electronic Information School Wuhan University Wuhan China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

In Wireless sensor networks (WSNs), ensuring the real-time and reliable collection of state information is crucial for maintaining the efficient operation of the network. To ensure freshness of information in delay-sensitive applications such as autonomous driving, this paper combines Unmanned Aerial Vehicle (UAV) and intelligent Reflecting Surface (IRS) technologies to deal with the IRS-aided UAV online data collection problem. In the formulated problem, the average Age of information (AoI) of sensor nodes (SNs) is minimized by jointly optimizing the IRS's phase shifts, the UAV's trajectory, and SN association. The problem is divided into two coupled subproblems: the IRS's phase control and UAV's data collection. We propose the framework of Proximal Policy Optimization (PPO) to deal with the two subproblems individually, referred to as PPO-Dual. In particular, given the UAV's position and SN association, the optimal phase shifts of the IRS is estimated using PPO based on the partial channel state information (CSI) obtained by sending pilot signals through some active elements mounted on the IRS. Based on the well trained IRS's phase estimation strategy, the UAV's online data collection scheme is also determined using PPO. Simulation results show that the proposed PPO-Dual algorithm can effectively estimate the IRS's phase shifts and achieve the average AoI performance close to that under perfect CSI conditions.

关键词： Wireless communication Wireless sensor networks Simulation Phase estimation Signal processing algorithms Data collection Autonomous aerial vehicles Trajectory Optimization Surface treatment

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Development of Dynamic Traffic Control Based on Congestion Level Using IoT

Development of Dynamic Traffic Control Based on Congestion L...

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International conference on Computer and Communications Technologies (ICCCT)

作者： T. Manju S. Sundar P. Edwin Richard R. Vishnu Vardhan M. Pavithran Dept of Information Technology Sri Sairam Engineering College Chennai India

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

Urban traffic congestion is a growing trend that leads to problems like pollution, prolonged delays, and vital risks, particularly for ambulances and fire engines. Primarily, traditional traffic management systems with fixed time-based traffic signals do not accommodate the dynamic nature of traffic, exacerbating these issues. Our project introduces an intelligent traffic light system powered by IoT sensors and Artificial intelligence algorithms to counter these situations as and when they arise. The system comprises two principal components namely: 1) infrared and radar sensors which keep watch over traffic intensity on various lanes, dynamically altered signal timings for alleviating the jam and 2) paving the way for ambulances by making automatic adjustments of the stream of road traffic to let them travel rapidly and securely. In as far as sensor processing data is involved, microcontrollers like STM32 are employed whilst Python and AI-driven algorithms take the role of decision-making. This is not only a way of alleviating urban transport congestion but also enhances road safety on the network leading towards smart sustainable cities.

关键词： Heuristic algorithms Urban areas Transportation Traffic control Market research sensor systems Road safety Delays Vehicle dynamics intelligent sensors

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AI Driven Rat Detection for Warehouse

AI Driven Rat Detection for Warehouse

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Emerging Smart Computing and Informatics (ESCI), conference on

作者： Ann Vincent Bhavesh Patil Aditya Murbade Hemalata Mote Shruti Mehata Dept. Elec and Telecomm. Engg. Don Bosco Institute of Technology Mumbai Mumbai India BharatGodam Solutions LLP Ahmedabad India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

The project’s goal is to create a system for controlling insect activity and monitoring of warehouses in sizable grain storage facilities. The idea behind the system uses neural networks, deep learning algorithms, and imagery processing methods to identify, monitor, track, and notify users of the activity of pests, notably rats, in real-time. By using algorithms that use deep learning for real-time object recognition and authentication, rats may be accurately identified. In addition, the sensors augment optical detection by using non-visual methods to detect motion and activity, providing full surveillance regardless of regions that are completely concealed. The system’s network of carefully positioned imaging devices and sensors allows for constant, continuous surveillance of the warehouse ambiance. The system activates and displays an indication once it recognises a rat, and it logs the precise time and place of the event. To ensure prompt action and response, warehouse administrators get updates in real time via email, SMS, or a mobile app. Through the application of artificial intelligence (AI), this initiative seeks to improve the security of food, reduce monetary damage, and revolutionize pest control at storage facilities for grain.

关键词： Deep learning Tracking Surveillance Neural networks Real-time systems sensor systems Optical sensors Object recognition Artificial intelligence intelligent sensors

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