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Energy performance of Internet of Things (IoT) networks for pipeline monitoring 20

Energy performance of Internet of Things (IoT) networks for ...

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20th IEEE international Wireless Communications and Mobile Computing (IEEE IWCMC) - Green and intelligent Communications

作者： Kuaban, Godlove Suila Czachorski, Tadeusz Gelenbe, Erol Pecka, Piotr Nkemeni, Valery Czekalski, Piotr Polish Acad Sci IITiS PAN Inst Theoret & Appl Informat Gliwice Poland Univ Buea Fac Engn & Technol Lab Elect Engn & Comp Buea Cameroon Silesian Tech Univ Fac Automat Control Elect & Informat Gliwice Poland

ISBN: (纸本)9798350361261;9798350361278

Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (primarily water, which is becoming a scarce resource) and environmental pollution (in the case of leakage of toxic fluids like oil and gas). Emerging technologies like the Internet of Things (IoT), Wireless Sensor Networks (WSNs), Artificial Intelligence (AI), distributed computing, and cloud computing enable continuous monitoring of pipelines to detect leakages and corrosion on the pipeline. The main challenge with using battery-powered sensor nodes to monitor pipelines is the energy constraint, necessitating frequent battery replacement. Thus, there is a need to develop energy-saving mechanisms to prolong the lifetime of these sensor nodes. In this paper, we use the diffusion approximation modelling framework in which the data from the experimental testbed are used to model the dynamics of the battery's energy content and to estimate the mean and variance of the device's lifetime. The novelty in the proposed diffusion model of the battery of an IoT node is the introduction of multiple energy thresholds that split the energy state-space of the battery into multiple energysaving regimes. As the battery discharges, the node gradually transitions into energy-saving regimes by reconfiguring some of its parameters to reduce energy consumption (sometimes at the cost of trading off some performance metrics). We investigate the impact of energy-saving regimes or the number of thresholds on the node's lifetime.

关键词： Green Internet of Things (IoT) energy performance diffusion models adaptive sensing distributed computing duty cycling

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An Overview of Power System Framework for Ensuring Scalability in Networks

An Overview of Power System Framework for Ensuring Scalabili...

引用

2023 international conference on Power Energy, Environment and intelligent control, PEEIC 2023

作者： Sharma, Rahul Kumar Jamal, Ahmad Thiruvenkadam, T. Noida Institute of Engineering and Technology Department of Computer Science Engineering Uttar Pradesh Greater Noida India Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Bangalore India

ISBN: (纸本)9798350357769

There is an increasing amount of integration occurring worldwide in different electric distribution networks between utility-owned / non-utility-owned (customer-owned) digital devices and systems. The development of distribution automation, microgrids, and self-healing systems are examples of utility-owned asset growth. On the other hand, non-utility-owned investments include solar electricity generating, electric cars, and behind-the-meter energy storage technologies. The flexibility and scalability of current centralized control systems are limited, making it difficult to properly integrate the growing variety and quantity of devices, even with the potential information and monitoring points provided by these installations. The limitations of latency, scalability, and connection capacity prevent these new gadgets and networks from actively participating as dynamic resources in the centrally controlled framework. In order to improve operational flexibility by coordinating centralized as well as distributed control systems, this article presents a standards-based architecture for distributed energy system controls. In order to improve resilience in the case of severe events and strengthen dependability during routine operations, the suggested system actively incorporates both utility also non-utility assets and uses a distributed design. The outcomes of field trials, complete information from a continuing full-scale deployment at Duke Energy, and laboratory test results are all included in the conclusions that are given. © 2023 IEEE.

关键词： centralized control distributed architecture distributed power system controls electric distribution systems microgrids OpenFMB and standards-based architecture operational flexibility resiliency self-healing systems

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Stree Mitra: Smart AI Device for Villages 15

Stree Mitra: Smart AI Device for Villages

引用

15th international conference on Advances in Computing, control, and Telecommunication Technologies, ACT 2024

作者： Kumar, Prasanna M.J. Gowda, Hemanth M.K. Monisha, H.P. Shalini, S. Poorvika, D.A. Computer Science & Engineering Department BGS Institute of Technology BG Nagar India

ISBN: (纸本)9798331300579

The creation and application of an intelligent vending machine with cutting-edge features for user convenience, medication dispensing, and sanitary pad dispensing ***, LCD display, keypad, RFIDtechnology, DC motor for dispensing, and Node MCU are used in the construction of the system for alerts about *** an LCD display and a keypad for simple interaction, the machine has an intuitive user *** on their individual needs, users can browse the menu to choose and buy sanitary pads or *** secure user authentication, RFID technology makes sure that only authorized users can access the vending *** dispensing mechanism uses a precision DC motor to guarantee that medications and sanitary pads are distributed precisely and under control.A disposal unit is part of the system to encourage environmental sustainability. © Grenze Scientific Society, 2024.

关键词： AC motors

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AI based Analysis of Hyperspectral Images with Spectacular Efficacy in Video Analytics

AI based Analysis of Hyperspectral Images with Spectacular E...

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2024 international conference on intelligent and Innovative Practices in Engineering and Management, IIPEM 2024

作者： Jadhav, Samarth Yogesh More, Rutuja Rajatam Tingare, Bhagyashree Ashok Lakshmi, G. Prasanna Kolse, Shivam Darwante, N.K. Sanjivani College of Engineering Department of Information Technology MH Kopargaon India D Y Patil College of Engineering Akurdi Department of Artificial Intelligence and Data Science Pune India Sandip University School of Computer Science and Engineering Maharashtra Nashik India Sanjivani College of Engineering Department of Electronics and Computer Engineering MH Kopargaon India

ISBN: (纸本)9798350390049

Hyperspectral imaging and artificial intelligence (AI) have transformed imaging and data processing through their ability to capture and analyze detailed spectral information. This paper explores the integration of hyperspectral imaging with AI, focusing on its impact on video analytics. Hyperspectral imaging provides comprehensive, multi-dimensional data by capturing a wide range of spectral wavelengths, enabling precise material identification and environmental monitoring beyond traditional RGB imaging. The synergy between hyperspectral imaging and AI enhances real-time analysis and decision-making by leveraging deep learning algorithms for pattern recognition and anomaly detection. This study introduces a novel AI-based hyperspectral image analysis approach for video analytics, utilizing convolutional neural networks (CNNs) and hybrid CNN-attention models to improve object recognition and classification. The methodology is validated through experiments that measure classification accuracy, processing speed, and resilience to varying conditions. Results demonstrate significant improvements in accuracy and efficiency over traditional methods, highlighting the potential for advanced applications in surveillance, environmental monitoring, and industrial quality control. © 2024 IEEE.

关键词： Convolutional neural networks

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Innovative System for environmental monitoring with Connected Sensors and Data Analysis for Chemical Pollutants

Innovative System for Environmental Monitoring with Connecte...

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2024 IEEE international conference on intelligent Systems and Advanced Applications, ICISAA 2024

作者： Suganya, A. Suryawanshi, Mahesh A. Bagal, Manisha V. Rawat, Ruchira Kaliappan, S. Manikandan, G. Karpagam College of Engineering Department of Information Technology Tamil Nadu Coimbatore India Bharati Vidyapeeth College of Engineering Department of Chemical Engineering CBD Navi Mumbai India Graphic Era Deemed to be University Department of Computer Science and Engineering Uttarakhand Dehradun India Lovely Professional University Division of Research and Development Punjab Phagwara India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331539948

The Chemical Pollutants system, which combines sophisticated data processing capabilities with networked sensors to identify and control chemical pollutants, transforms environmental monitoring. It collects real-time data on pollutants using extremely accurate sensors, which are then evaluated using cloud infrastructure and a reliable wireless connection. Predictive insights using machine learning algorithms provide notable improvements: 97% accuracy in sensor data, 3 seconds of data transmission latency, and 99.5% system uptime. There are now 1200 daily active users, and the prediction model's accuracy is 92%. environmentally, it resulted in a 30% decrease in PM2.5 levels, a halving of high pollution alerts to 10 per month, and an 85% increase in public awareness. The number of policy changes tripled to four each year, while community engagement quadrupled to twelve. The results highlight the system's contribution to improving the timeliness and quality of environmental data, influencing public health and policy, and highlighting its efficacy and potential for wider environmental management use. © 2024 IEEE.

关键词： Volatile organic compounds

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Next-Gen Energy Management: IoT Gateway for Smart monitoring and Appliance control 6

Next-Gen Energy Management: IoT Gateway for Smart Monitoring...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Kabra, Sohum Nadagouda, Prithvi Nikam, Yash Kavedia, Manoj S. Thadomal Shahani Engineering College Mumbai India Thadomal Shahani Engineering College Mumbai India

ISBN: (纸本)9798331522667

This research study proposes an IoT-based solution for intelligent energy management, designed to monitor and optimize power consumption in both residential and industrial environments. The system will integrate an AI meter for real-time tracking of voltage, current, and power usage, alongside environmental sensors that measure parameters like temperature, humidity, light intensity, and motion. These data inputs are processed by an IoT gateway based on an ESP32 microcontroller and Raspberry pi, which will handle the data locally or transmits it to a cloud-based or edge machine learning model. The machine learning model analyzes real-time sensor data combined with historical consumption patterns to predict and implement optimal appliance control strategies. The system aims to reduce power consumption by up to 20-25%, contributing to energy efficiency without compromising operational performance and delays. Appliances are controlled remotely using IR Blasters and relays, allowing for dynamic, real-time adjustments based on environmental factors. The solution is scalable, making it applicable for both household energy management and large-scale warehouse automation. By utilizing predictive analytics and intelligent control, the system optimizes energy usage, offering a sustainable, automated solution for modern smart homes and industries. This integration of IoT and machine learning provides a significant step toward more efficient and sustainable energy management practices. © 2025 IEEE.

关键词： Gateways (computer networks)

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Design of RTOS-based Wireless Remote monitoring System for Indoor Environment 12

Design of RTOS-based Wireless Remote Monitoring System for I...

引用

12th international conference on Networks, Communication and Computing (ICNCC)

作者： Zhu, Peizhi Li, Dajun Guo, Lihui Lin, Fanqiang Chengdu Univ Technol Chengdu Peoples R China

ISBN: (纸本)9798400709265

With the development of low-cost microcontrollers, sensors and wireless communications, intelligent environment monitoring based on the Internet of Things (IoT) has become possible. In this paper, an indoor environment monitoring system constructed by sensor network is realized. The system consists of distributed sensing nodes, which contain temperature and humidity, human infrared, voice recognition and camera sensors, etc. The nodes are connected to STM32 microcontrollers and WIFI modules and are scheduled in real time using free real time operating system(FreeRTOS). The visual and time series sensing data are transmitted to the server via WIFI in real time, and the user can monitor the system remotely by using the PYQT interface program on the PC. The system can also control home appliances by voice. The data interaction uses self-built WIFI module in AP mode for SOCKET communication. Through rigorous testing, the system demonstrates the capability of data communication, low-latency video streaming, and bidirectional control. The sensor network and real-time OS based architecture utilizes parallel execution to balance different temporal tasks and realize an agile cyber-physical system. This paper provides a reference for the underlying software infrastructure of intelligent buildings, embodying the integrated application of real-time scheduling, sensor networks and human-computer interaction.

关键词： Internet of Things Real Time Operating System Sensor networks WIFI STM32 data acquisition

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Optimizing environmental Parameters in Smart Greenhouse Design with IoT and Sensor Networks 1

Optimizing Environmental Parameters in Smart Greenhouse Desi...

引用

1st IEEE international conference on Computing and Data Science, ICCDS 2024

作者： Raro, Edralin R. Palaoag, Thelma D. College of Agriculture and Natural Resources Camarines Norte State College Daet Camarines Norte Philippines College of Information Technology and Computer Science University of the Cordilleras Gov. pack road Baguio City Philippines

ISBN: (纸本)9798350365337

This paper explores contemporary agricultural practices and cutting-edge technologies to improve crop yields. Implementing an intelligent greenhouse model that automates farm tasks, minimizing manual intervention. The closed structure of the greenhouse shields plants from adverse weather conditions such as temperature extremes, humidity fluctuations, and variations in air and soil moisture. The study introduces an innovative automatic irrigation system to address the shortcomings of traditional agricultural irrigation methods, emphasizing efficient water consumption control and energy utilization. The proposed system integrates a distributed wireless sensor network, including soil moisture, humidity, and temperature sensors, utilizing the Blynk cloud-based IoT platform and ThinkSpeak, Soil moisture and temperature sensors feed data to NodeMCU V3 ESP8266 WiFi transceiver module controller, A key feature is integrating Android applications and web servers, enabling remote control and monitoring. This technological innovation ensures control over water and energy resources and changes climates, thereby creating sustainable and technologically driven agrarian practices. © 2024 IEEE.

关键词： Soil moisture

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Research on environmental monitoring and Prediction Method of Orchard Frost Based on Wireless Sensor Network

Research on Environmental Monitoring and Prediction Method o...

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international conference on Guidance, Navigation and control, ICGNC 2022

作者： Ding, Hao Liu, Limin Liang, Zhao College of Mechanical and Architectural Engineering Taishan University Tai’an27100 China College of Science China Agricultural University Beijing100193 China School of Information Science and Technology Taishan University Tai’an27100 China

ISBN: (纸本)9789811966125

The meteorological conditions of orchards will directly affect the yield and quality of fruits, and in order to reduce the yield and quality reduction caused by environmental disasters, it is necessary to carry out research work on intelligent monitoring and prediction methods of orchard frost environment. Based on the Internet of Things, the study of orchard frost environment can be based on intelligent monitoring and combined with prediction methods to sense orchard environmental data as comprehensively and in real time as possible, to achieve accurate and comprehensive evaluation of the environment and reasonable and effective prediction of environmental change trends, which has important theoretical research significance and wide application prospects. The paper focuses on several aspects involved in environmental monitoring, and on the basis of designing the overall architecture of the monitoring system, it mainly researches the orchard environmental monitoring network, builds a wireless sensor network, designs an environmental monitoring data fusion algorithm based environmental change prediction model. The experiments show that the intelligent monitoring system is able to analyze and deal with potential hazards facing the orchard environment, while having a distributed and scalable network architecture to meet the system's real-time response requirements;in terms of prediction, it is able to achieve early warning of disaster weather. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Network architecture

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intelligent Farming: IoT-Powered System for Efficient Soil Condition Analysis 13

Intelligent Farming: IoT-Powered System for Efficient Soil C...

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13th international conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Sisodia, Ankur Vishnoi, Swati Sharma, Nandini Singh, Shiv Shanker Khenwar, Medha Gupta, Priyanka Gla University Department of Computer Engineering and Application Mathura India Banasthali Vidyapith Department of Computer Science Rajasthan India G.L. Bajaj Group of Institutions Department of Computer Science and Engineering Mathura India Sanskriti University Department of Computer Science and Engineering Mathura India

ISBN: (纸本)9798350380583

Smart farming technology allows farmers to control and analyse variables in real-time, helping them optimize crop growth and manage their operations more efficiently. The use of specialized sensors, data collection tools, and advanced analytics in Internet of Things (IoT) systems is helping to bridge the gap between physical farm conditions and digital monitoring. In this study, we aim to develop a system that monitors soil conditions to support smart farming. The system provides farmers with live data on key environmental factors, such as temperature, humidity, soil moisture, and soil temperature, to improve crop yield and product quality. The IoT setup for this intelligent farming solution includes components like the DHT11 and humidity sensors, a DS18B20 temperature probe, LDR, water pump, and a 12V LED strip, all controlled by a NodeMCU. When the system is activated, it continuously monitors soil and environmental conditions and sends this information to the cloud for real-time access. If the soil moisture falls below a set threshold, the system automatically triggers irrigation. Our experimental results show that this model improves decision-making for managing farming conditions. © 2024 IEEE.

关键词： Smart agriculture

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