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LoRaWAN Enabled Smart Landslide Early Detection and Alerting

LoRaWAN Enabled Smart Landslide Early Detection and Alerting

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International conference on Computer and Communications Technologies (ICCCT)

作者： Y. Harshith M. Nitheesh Kumar Yamini B Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

Landslides are a very hazardous risk to human life, infrastructure, and the environment as well. Highly accurate early warning systems are therefore required for risk reduction. The subsequent research proposal aims to create an AI and IoT-based land-slide prediction and early warning system based on selection of various sensors like MEMS accelerometers and tilt sensors, piezoelectric sensors, soil moisture sensors, rainfall detector, and temperature sensors. These sensors will be continuously monitoring Hydrological, Metrological, Geomechanical parameters are used for monitoring probable causes of landslides. sensor data will be analyzed by machine learning algorithms for land-slide prediction and past trends. The system will be having edge processing for real-time monitoring and early warning through alarm on mobile, siren, and warning of disaster management authorities. This project aims to develop an affordable, highly accurate, and scalable landslide prediction system by integrating sensor networks, IoT, AI and LowRaWAN. A pilot deployment in landslide-prone regions will assess its field performance and reliability. By delivering real-time, dependable landslide alerts, the system will enhance disaster preparedness, minimize casualties, and streamline evacuation planning.

关键词： Temperature sensors Landslides Accuracy Disasters Soil moisture LoRaWAN sensor systems Terrain factors Monitoring intelligent sensors

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PNN-Based Condition Monitoring Method for Shield Machine Roller Blades

PNN-Based Condition Monitoring Method for Shield Machine Rol...

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Asia-Pacific conference on intelligent Robot Systems (ACIRS)

作者： Chongru Wang Qiang Gao Youfu Wang Chenxu Yang Junzhou Huo School of Mechanical Engineering Dalian University of Technology Dalian China

ISBN: (数字)9798350352573

ISBN: (纸本)9798350352580

In recent years, multi-sensor information fusion technology has been widely used in more and more fields. This technology is rarely used in the field of tunneling, especially in the monitoring of hob state. Most of the methods are finite element simulation and single sensor measurement, and the accuracy of the results will decrease in dealing with complex working conditions. In this paper, a variety of sensors are used to monitor hob information and environment, and a method based on PNN (Probabilistic Neural Network) is proposed to fuse the information of each sensor, and the trained network is used to judge the hob state, and the prediction accuracy is compared with that of a single sensor. The results show that this method can better reflect the state of hob driving under bad working conditions.

关键词： Employee welfare Condition monitoring Accuracy Neural networks Tunneling Robot sensing systems Probabilistic logic

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Research on intelligent Training System of Athletes Assisted by Computer and Cloud Computing 3

Research on Intelligent Training System of Athletes Assisted...

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3rd International conference on Computers, information processing and Advanced Education, CIPAE 2022

作者： Xie, Yu Liu, Lu Chengdu University of Information Technology Department of Physical Education Chengdu China Chengdu University of Information Technology Chengdu China

ISBN: (纸本)9781665468121

Collection work is the key to the training level of athletes in the process of track and field sports training. This paper applies the idea of multi-sensor to information fusion technology. In this paper, the critical indicators of athletes are collected through multiple sensors and cameras. The former is to use wavelet transform to realize the feature extraction of human surface EMG signals. Then this paper uses the artificial neural network method to identify the key features to get the preliminary track and field evaluation results. The research found that this method can measure the training rotation angle, motion characteristic data trajectory, speed, acceleration, and other indicators in real-time and accurately determine the difference. The motion acquisition technology proposed in this paper can correct bad habits and improve the training level. © 2022 IEEE.

关键词： Wavelet transforms

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On Solving Area Coverage for Heterogeneous Directional sensor networks

On Solving Area Coverage for Heterogeneous Directional Senso...

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International conference on Electrical Engineering/Electronics, Computer, Telecommunications and information Technology, ECTI-CON

作者： Thaschakorn Sungvornyothin Mason Thammawichai Electrical Engineering Department Navaminda Kasatriyadhiraj Royal Air Force Academy Saraburi Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

Wireless sensor networks play important roles in the intelligent systems of current technology, such as the Internet of Things (IoT). The heterogeneous directional sensor network (HDSN), which contains a large number of sensor nodes with different capabilities and is limited in sensing direction, has become more realistic in many applications. However, most existing works in the literature focus on homogeneous and omni-directional sensor networks, which cannot be efficiently applied to real-world applications. Therefore, in this study, we propose a novel algorithm called the Van der Waals Force-Based Algorithm for Heterogeneous Directional sensor networks (VW-HDSN) to solve the coverage problem in HDSNs. The simulation results illustrate that our algorithm can achieve a superior coverage ratio compared to that of a random approach by 18.66%. The results also suggest that adding efficient nodes to the network will significantly improve its performance. Another benefit of our algorithm is that it can be generalized to a fully heterogeneous network where all nodes are diverse in angle of view and sensing radius.

关键词： Wireless sensor networks Simulation Scalability Force Robustness sensors Telecommunications

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AutoGrAN: Autonomous Vehicle LiDAR Contaminant Detection using Graph Attention networks 15

AutoGrAN: Autonomous Vehicle LiDAR Contaminant Detection usi...

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15th ACM/SPEC International conference on Performance Engineering (ICPE)

作者： Jati, Grafika Molan, Martin Khan, Junaid Ahmed Barchi, Francesco Bartolini, Andrea Mercurio, Giuseppe Acquaviva, Andrea Univ Bologna DEI Dept Bologna Italy FEV Italia Srl Turin Italy

ISBN: (纸本)9798400704451

Extreme conditions and the integrity of LiDAR sensors influence AI perception models in autonomous vehicles. Lens contamination caused by external particles can compromise LiDAR object detection performance. Automatic contaminant detection is important to improve reliability of sensor information propagated to the user or to object detection algorithms. However, dynamic conditions such as variations in location, distance, and types of objects around the autonomous vehicle make robust and fast contaminant detection significantly challenging. We propose a method for contaminant detection using voxel-based graph transformation to address the challenge of sparse LiDAR data. This method considers LiDAR points as graph nodes and employs a graph attention layer to enhance the accuracy of contaminant detection. Additionally, we introduce cross-environment training and testing on real-world contaminant LiDAR data to ensure high generalization across different environments. Compared with the current state-of-the-art approaches in contaminant detection, our proposed method significantly improves the performance by as much as 0.1575 in F1-score. Consistently achieving F1 scores of 0.936, 0.902, and 0.920 across various testing scenarios, our method demonstrates robustness and adaptability. Requiring 128 milliseconds on a AMD EPYC 74F3 CPU for the end-to-end process, our method is well-suited for an early warning system, outperforming human reaction times, which require at least 390 milliseconds to detect hazards. This significantly contributes to enhancing safety and reliability in the operations of autonomous vehicles.

关键词： Advanced driver assistance systems (ADAS) autonomous vehicle perception systems LiDAR Point Cloud reliability LiDAR contamination and Noise detection Graph processing Graph Attention networks

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An Overview on Advancements in Water Leakage Detection Integrating Cutting-Edge Solutions

An Overview on Advancements in Water Leakage Detection Integ...

引用

International Workshop on Research and Education in Mechatronics (REM)

作者： Ala' Khalifeh Nowfal Aweisi School of Electrical Engineering and Information Technology German Jordanian University Amman Jordan

ISBN: (数字)9798331505974

ISBN: (纸本)9798331505981

Water leakage pose a significant challenge to the sustainability of water resources and infrastructure around the world. In response, this paper presents an overview of the latest advances in water leakage detection techniques, encompassing both hardware and software methodologies. The hardware section examines state-of-the-art sensors and tools used for data collection in water leakage detection systems. Various sensor technologies have been explored including acoustic, electromagnetic, water flow, and pressure sensors. Additionally, innovative tools such as robots and remote sensing technologies are being explored for their potential to improve the efficiency of leak detection operations. At the same time, the software aspect of water leakage detection is explored, focusing on the algorithms used to analyze the data collected by the sensors. The effectiveness of advanced signal processing techniques, machine learning algorithms, and artificial intelligence models in identifying and locating leaks in water distribution networks is examined. Additionally, data fusion methods are explored to integrate information from multiple sensors and increase the reliability of leak detection systems. By synthesizing the latest developments in the hardware and software domains, this review provides valuable insights into the changing landscape of water leakage detection technologies. The integration of advanced sensors with advanced data analysis algorithms offers promising opportunities to improve the efficiency, accuracy, and reliability of leak detection systems, thereby contributing to the sustainable management of water resources.

关键词： Machine learning algorithms Software algorithms Signal processing algorithms Software sensor systems Hardware Software reliability Leak detection Water resources intelligent sensors

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Eclipse: An End-to-End Platform for Low-Cost, Hyperlocal Environmental Sensing in Cities 21

Eclipse: An End-to-End Platform for Low-Cost, Hyperlocal Env...

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21st ACM/IEEE International conference on information processing in sensor networks (IPSN)

作者： Daepp, Madeleine I. G. Cabral, Alex Ranganathan, Vaishnavi Iyer, Vikram Counts, Scott Johns, Paul Roseway, Asta Catlett, Charlie Jancke, Gavin Gehring, Darren Needham, Chuck von Veh, Curtis Tran, Tracy Story, Lex D'Amone, Gabriele Nguyen, Bichlien H. Microsoft Res Redmond WA 98052 USA Harvard SEAS Cambridge MA USA Univ Washington Seattle WA 98195 USA Univ Illinois Discovery Partners Inst Chicago IL USA

ISBN: (纸本)9781665496247

This paper presents Eclipse, a platform for low-cost urban environmental sensing using solar-powered and cellular-connected devices. Dense sensor networks promise to monitor pollution at fine spatial and temporal resolutions, yet few cities have actually implemented such networks due to high costs and limited accuracy. We address these barriers by developing an end-to-end framework for urban air quality sensing with minimal infrastructure requirements. We designed an unobtrusive device that collects data on fine particulate matter (PM2.5), temperature, relative humidity, and barometric pressure. A modular design further includes four low-cost gas sensors - Ozone (O-3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), and Carbon Monoxide (CO) - selected based on local priorities. We deployed 115 devices across Chicago, reliably collecting data for over 90% of expected sensor-hours from July 2 - September 30, 2021. We further developed a calibration strategy that reduced errors by 41.2 - 98.8%, improving accuracy to levels recommended for hotspot detection (PM2.5 and O-3) or education (NO2 and SO2). Through this work, we offer insights on the real-world deployment of a replicable, large-scale, end-to-end platform for hyperlocal urban environmental sensing.

关键词： Internet of Things Air Pollution Smart Cities sensor networks

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intelligent Substation IOT System design based on edge computing 2

Intelligent Substation IOT System design based on edge compu...

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2nd International conference on Electronic Materials and information Engineering, EMIE 2022

作者： Zheng, Yiming Qian, Ping Lin, Jiajun Li, Chen He, Wenlin State Grid Zhejiang Electric Power Co. Ltd. Research Institute Zhejiang Hangzhou310014 China State Grid Zhejiang Electric Power Co. Ltd. Zhejiang Hangzhou310000 China

ISBN: (纸本)9781713865629

The smart substation accesses a large number of sensor devices to sense the parameters of the substation equipment, and the current substation IOT system mainly calculates and processes the accessed sensor data in the data center, resulting in high computational pressure on the data center side and low bearing capacity of the IOT system. To address the above problems, the intelligent substation IOT system based on edge computing is designed. The hardware architecture of the IOT system is designed in the form of PMB7900 plus microcontroller dual core. Under the hardware support, the substation IOT edge computing system is designed to achieve flexible access to the IOT system by processing the state sensing of substation sensing devices during their life cycle and realizing multiple sensors. The system performance test results show that the designed system has good carrying capacity and the system processing time is shortened by about 63.2%, which is a significant performance improvement compared with other systems. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Edge computing

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An intelligent wireless monitoring system in telemedicine using IOT technology 10

An intelligent wireless monitoring system in telemedicine us...

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10th International conference on Modern Power Systems, MPS 2023

作者： Zanaj, Elma Basha, Gledis Biberaj, Aleksander Balliu, Lorena Polytechnic University of Tirana Faculty of Technology of Information Tirana Albania

ISBN: (纸本)9798350326826

Patient monitoring in healthcare is an important solution to get biometric values. Measurement and display of multiple biometric values such as heart rate, temperature, SpO2, respiration, ECG, etc., is necessary to determine the actual well-being of the patient. This approach is usually implemented in a hospital environment. Population aging and health changes in older patients rises a need for constant monitoring not only in hospital environment but also in every facility where elders live. Monitoring of their activity alongside with biometric values can improve the rate of disease control, lower healthcare costs, faster diagnosis, and lower medical service queue. Wireless sensor Network (WSNs) play a substantial role in implementing this technology. The proposal in this paper is to create a wireless network of low-cost sensors capable of gathering all the patient physiological data, transmitting this information throw IoT technology for distance monitoring. Creating this approach can help in minimizing the number of social workers in elder facilities but in the same time having a better view of specific disorders in early stages. Using IoT for being able to access the information can help also in analyzing this data, setting some ranges in values we can generate alarms and also start early treatment relying in the data processing. © 2023 IEEE.

关键词： Disease control

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IoT-Driven Smart Healthcare Systems for Remote Patient Monitoring and Management

IoT-Driven Smart Healthcare Systems for Remote Patient Monit...

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intelligent Technologies (ACOIT), Asian conference on

作者： Ram Madunuri Subrahmanyasarma Chitta Venkata Sri Manoj Bonam Vinay Kumar Reddy Vangoor Sai Manoj Yellepeddi Chetan Sasidhar Ravi Data Science Tata Consulting Services Hyderabad India Access2Care LLC Denver Colorado USA New York Life Insurance New York USA Metasofttech Solutions LLC Phoenix Arizona Zurich Insurance Company Schaumburg IL

ISBN: (数字)9798350374957

ISBN: (纸本)9798350374964

Internet of Things (IoT) has come to stay in healthcare whereby this advanced technology has drastically changed remote patient monitoring and management which has paved way for enhanced effective, affordable and patient centered approach to care delivery. This paper describes IoT-based smart health care system to improve the quality and effectiveness of patient care through the integration of wearable devices and sensors that are used to monitor the patient’s health status in real-time. The collected data is transmitted through secure data networks to the cloud-analysis blocks in which sophisticated analytical algorithms work to analyze the available data and provide suitable information. As illustrated in the result section, obtained results show that there is a enhancement of previous systems by up to $\mathbf{1 5 \%}$ on monitoring accuracy, that the response time for data processing has been reduced by $\mathbf{2 5}$ milliseconds and that there is a $\mathbf{2 0 \%}$ increase in patients satisfaction. It also has the ability of outputting a $\mathbf{3 0 \%}$ decrease on false alarms and a decrease of 15% on total healthcare expenses. These findings come as a proof that IoT has a capability of revolutionizing healthcare through early identification of risky conducts and timely medical treatments.

关键词： Patient monitoring Accuracy Medical services Data processing Real-time systems sensor systems Internet of Things Wearable devices Wearable sensors intelligent sensors

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