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Cloud-Based Solar Lights for Sustainable Cities: Real-time monitoring and Energy Efficiency Solutions 2

Cloud-Based Solar Lights for Sustainable Cities: Real-time M...

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2nd international conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Raman, Ramakrishnan Presitha Aarthi, M. Vekariya, Daxa Naikade, Kshitij Ranganath Sujatha, S. Maharashtra Pune India Department of Computer Science and Engineering Shree Sathyam College of Engineering and Technology Salem Tamil Nadu Sankari India Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Gujarat Vadodara India Maharashtra Pune India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350305418

The real-time sensor data improves energy efficiency and optimizes solar-powered lighting to increase urban sustainability. Due to increasing energy needs and environmental concerns, sustainable alternatives such as solar lighting are becoming essential in significant cities. These bulbs provide a feasible solution for usual lighting systems, reducing harmful carbon emissions while helping to build sustainable cities. The system's ability to monitor and control its environment in real-time is based on the cautious positioning of a wide variety of sensors connected with raspberry pi. Light, motion, temperature, and battery life sensors can be integrated for real-time monitoring and control, improving efficiency and developing environmentally friendly urban environments. Collectively, these sensors input information into the cloud-based system in real-time, offering a wealth of information for analysis and decision-making. Remote monitoring and management on the cloud platform enable fast changes and resource efficiency. Innovative methods may continuously light levels based on the collected sensor data to optimize efficiency without reducing lighting quality. The system adjust to changing conditions, such as weather levels, significantly improves its efficiency and lifetime. The technology can reduce energy costs, promote sustainable urban growth, and create greener, more environmentally aware cities by using real-time data and intelligent control mechanisms. © 2023 IEEE.

关键词： Cloud computing Energy Efficiency Remote monitoring Sensors Solar lights

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distributed monitoring and control System of Gas Concentrations in Different Environment

Distributed Monitoring and Control System of Gas Concentrati...

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international conference on control Systems and computer Science (CSCS)

作者： Iulian Furdu Eusebiu Pruteanu Costică Nițu Department of Mathematics and Informatics University Vasile Alecsandri of Bacau Bacau Romania Department of Energy and Computer Science University Vasile Alecsandri of Bacau Bacau Romania Department of Intelligent Robotics) Polytechnic University) Bucharest Romania

Wireless Sensor Systems (WSN) is a broad, exciting area with new perspectives and growing growth over the past decades, where more research is being done. WSNs contain many (hundreds of thousands) of micro-sized, cheap chips, powered by low-cost wireless interconnected batteries. These chips are called nodes, which could be of several types, including acoustic, radar, low-frequency magnetic, thermal, and visual sampling frequencies. Many applications are based nowadays on WSN, such as environmental control, smart cities, wildlife monitoring, vehicles and infrastructure, natural disasters, home security, underwater investigations, military, airplane surveillance and drone body sensors. One of the aims of the paper is to develop a smart architecture based on intelligent microprocessor sensors, WSN802GCA/GPA and the software needed to operate with a TINI control unit. TINI allows this system to be connected to Ethernet via TCP/I$\mathbf{P}$

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Comprehensive Evaluation of Rail Transit Hub Transfer Based on AHP 3

Comprehensive Evaluation of Rail Transit Hub Transfer Based ...

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3rd international conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Nie, Kun Architecture and Environmental Engineering Dongying Vocational Institute Shandong Dongying China

Research background: With the development of science and technology and the intelligence of the construction industry, the traditional extensive construction method can no longer meet the social demand for safety, which requires the construction enterprises and construction units to constantly change the safety management mode. With the advancement of urbanization, intelligent management and control has become the future development direction of the construction industry, and BIM software has also become an important synchronization platform, which will continuously improve the promotion of the overall project and the management of construction safety. Research methods: This paper mainly uses literature survey, quantitative and qualitative analysis, empirical analysis and other methods, which can study the construction safety management and intelligent management and control as a whole. Through literature survey, this paper has obtained a large amount of literature, which can enrich theoretical analysis and comprehensively understand the current construction safety management mode and intelligent management and control mode. Through relevant theories, this paper can fully demonstrate the follow-up research and empirical analysis. Through quantitative and qualitative analysis method, this paper can use statistical analysis method to analyze construction safety accident data, which will analyze the internal relationship through relevant software. Therefore, the quantitative and qualitative analysis method provides important data support for the subsequent research, which can provide statistical methods for the analysis of building safety hazard sources. Through the empirical simulation method, this paper can analyze specific projects with real cases, which will truly simulate the intelligent monitoring system. Through the empirical simulation method, this paper can verify the scientific nature of the algorithm, and can also demonstrate the management and control mode

关键词： Construction industry

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Internet of Robot Things in a Dynamic Environment: Narrative-Based Knowledge Representation and Reasoning 18th

Internet of Robot Things in a Dynamic Environment: Narrative...

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18th European-Alliance-for-Innovation (EAI) international conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous)

作者： Lyazid, Sabri Univ Paris Est Lab Images Signals & Intelligent Syst LISSI Champs Sur Marne France Univ Mohamed El Bachir El Ibrahimi Comp Sci Dept BBA El Anceur Algeria

ISBN: (纸本)9783030948221;9783030948214

Internet of Things (IoT) technologies interconnect increasing numbers of artifacts (e.g., robots, sensors) and individuals, allowing the setting up of Internet of Robotic Things (IoRT) systems in a dynamic environment (e.g., homes, hospitals). Semantic heterogeneity is among the main challenges that arise for developing those systems. Particularly to deal with the dynamic knowledge extraction from the heterogeneity of sensors and data that are spatially and temporally distributed, the sporadic occurrence of events, and also if there is a causality chain that explains an ordered occurrence of these events. Ontologies constitute de facto an ineluctable design to reduce this ambiguity by creating a semantic link between low-level digital data, allowing: i) dynamic knowledge management, and ii) enhancing environmental perception and anchoring functions. This approach uses a model that overcomes the disadvantages of the semantic Web standards such as OWL/RDF-S. An IoRT system dedicated to monitoring and assisting the elderly in their everyday living is described and evaluated.

关键词： Ontology OWL Narrative Reasoning Spatial-temporal representation IoRT IoT distributed systems

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IoT-based environmental monitoring System

IoT-based Environmental Monitoring System

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intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： D. Abhiram K. Dhanush Reddy P. Koushik Reddy Meena Belwal Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

This project meets the current important demand for the constant monitoring of environmental conditions because climate change and human activities affect ecosystems. Temperature and humidity are measured using the DHT11/DHT22 sensor connected to the ESP8266 microcontroller and the GPS module is used to obtaining the location information. In contrast to current approaches targeting the communication data or energy consumption only, the contaminants of this system are unified, location-based, and central. It provides immediate data transfer to the cloud through a comfortable low power interface for usage in farming, transportation, and more for environmental monitoring. The findings show that all the environmental conditions and location change can be monitored by the IoT-based system which use ESP32/Arduino microcontroller for sensing data by a Bluetooth or Wi-Fi through cloud platform or server and it gives alert message to web interface or mobile application when temperature increases or decreases more than threshold values. This practical system is especially valuable for those areas of interest that require a constant check, such as environmental control or the logistics and health safety of the transported goods or passengers.

关键词： Climate change Internet of Things environmental monitoring Embedded systems intelligent sensors Data processing Air quality

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intelligent Load control with Embedded Automation and Mobile Application

Intelligent Load Control with Embedded Automation and Mobile...

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distributed Computing and Optimization Techniques (ICDCOT), international conference on

作者： Kalyan Dusarlapudi Appana Naga Suresh Basa Naveen Komarina Lakshmi Likhitha EEE Department Koneru Lakshmaiah Education Foundation Guntur India CSE Department Koneru Lakshmaiah Education Foundation Guntur India

The escalating rate of energy consumption and its adverse environmental effects, coupled with the reliance on non-renewable sources like fossil fuels, has heightened the importance of energy management. The framework for “intelligent Load control with Embedded Automation and Mobile Application” is presented, emphasizing the optimization of energy consumption. Utilizing Long short-term memory (LSTM) model from deep learning, to implement energy generation forecasting. These precise forecasts interface with an advanced load scheduling algorithm implemented by using Autoregressive Integrated Moving Average (ARIMA) Model, prioritizing loads based on priority matrix technique and efficiently scheduling loads based on predefined criteria and temporal proximity. Further, a controller enables dynamic load shifting between renewable sources and the grid further this will control the loads as per scheduled timetable, enhancing overall energy utilization. The integration of these methodologies, along with a mobile application for real-time monitoring, establishes an intelligent system poised to significantly improve energy efficiency and promote sustainable practices in the context of embedded automation and mobile applications.

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IoT and computer Vision Based Aquaponics System 24

IoT and Computer Vision Based Aquaponics System

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24th IEEE/ACIS international Winter conference on Software Engineering, Artificial Intelligence, Networking and Parallel/distributed Computing, SNPD 2022

作者： Ahmad, Nazib Hasan, Md. Mehedi Rohomun, Mhamudur Irin, Raihana Rahman, Rashedur M. North South University Department of Electrical and Computer Engineering Plot-15 Block-B Bashundhara Dhaka-1229 Bangladesh

ISBN: (纸本)9798350310412

A farming method known as aquaponics aims to be a more effective response to the world's worries about food production and scarcity. In order to produce plants or vegetables in addition to fish to meet the rising global demand for food, this technique combines aquaculture (fish farming) and aquaponics (plants grown without soil). This technique or system promises to utilize less water, fertilizer, pesticides, and space while yet producing as much as conventional farming. The challenge is making it more usable and scalable for commercial and public use. To overcome such challenges, this technique must be intelligent and automated by rigorous sensing, monitoring, and system control. Our current research aims to develop a practical smart IoT-based aquaponics system. It offers a workable solution and ideas for further investigation while also looking for gaps in the earlier investigations. © 2022 IEEE.

关键词： Fish

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Enforcing the Security and Usability of Blockchain for a Smart City Cyberinfrastructure

Enforcing the Security and Usability of Blockchain for a Sma...

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2024 international Russian Automation conference, RusAutoCon 2024

作者： Kalinin, Maxim Busygin, Alexey Konoplev, Artem Institute of Computer Sciences and Cybersecurity Peter the Great St.Petersburg Polytechnic University St.Petersburg Russia

The development of smart cyberinfrastructures on the basis of the Internet of Things has caused the penetration of new technologies into the spheres of unmanned transportation, robotic buildings, and digital economy, and then, as a result of the integration of cyber-physical systems with monitoring, analytical, and control means, a new intelligent urban paradigm of a 'smart city'. Noting the high criticality of this system, specific threats are aimed at disrupting its connectivity, resource capturing, functional availability, data privacy, and safety. As a protective measure, blockchain is a usual part of the security arsenal of any distributed system, providing provable security to all its participants. However, in a large-scale smart city's cyberinfrastructure, blockchain itself becomes a target of specific cyber threats, e.g., a '51% attack'. Also, the blockchain's usability issue is the unlimited growth of its structure, leading to exhaustion of free resources and thus depressing its use. Conventional approaches to preventing the blockchain from these issues downgrades its scalability and therefore are not widely applicable in a smart city. This paper proposes a new technique to protect the blockchain applied in a large-scale smart city network infrastructure. The proposed solution combines assessing the intruder's capabilities and providing dynamic adaptation of the blockchain to evolving threats. To avoid infinite growth of the blockchain, the blockchain with a floating genesis block and fixing blocks has been implemented. The developed modifications retain the ability to scale the blockchain. The experimental study has demonstrated the effectiveness of the proposed approach. © 2024 IEEE.

关键词： Network intrusion

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AI-Driven Smart Irrigation: Enhancing Agricultural Water Efficiency Through intelligent Valve Regulation in Piped and Micro Irrigation Networks 1

AI-Driven Smart Irrigation: Enhancing Agricultural Water Eff...

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1st international conference on Pioneering Developments in computer Science and Digital Technologies, IC2SDT 2024

作者： Alex, B. Jignasa, G. Madhubabu, K. Gopi, A. School of Electrical and Electronics Lovely Professional University Punjab India

ISBN: (纸本)9798350365016

This paper presents a revolutionary solution to optimize water use in agriculture, using an AI-based smart irrigation system. Our approach focuses on automatic adjustment of water release control valves, guided by artificial intelligence (AI) that takes into account the complex relationship between soil moisture and ambient temperature in the plant root zone. The decision-making process in our system is powered by a deep neural network meticulously trained on a comprehensive dataset, including the dynamic interaction of soil moisture, temperature changes of the crop. The reason for using an AI model that focuses specifically on the relationship between soil moisture and temperature lies in its ability to recognize small details, complex patterns and correlations that impact irrigation need. Traditional methods are often unable to adapt to the complex and dynamic nature of agricultural ecosystems. By harnessing the power of AI, our system not only captures, but also learns and predicts, optimal irrigation conditions, thereby promoting resource-efficient agricultural practices. The proposed system seamlessly integrates with micro-irrigation and pipeline networks, ensuring flexibility in different agricultural environments. Using MQTT communication powered by Node-RED, collected data is efficiently transmitted to the cloud, allowing real-time monitoring and analysis. This combination of AI, sensor technology and cloud connectivity aims to provide farmers with accurate information, promote water conservation, optimize crop yields and reduce environmental impact. Ultimately, our research contributes to advancing sustainable agriculture by addressing important challenges and paving the way for a new era of smart irrigation practices. © 2024 IEEE.

关键词： Soil moisture

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An intelligent and Cost-Effective IoT-Based Irrigation System Using Machine Learning 2

An Intelligent and Cost-Effective IoT-Based Irrigation Syste...

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2nd international conference on Disruptive Technologies, ICDT 2024

作者： Kadiyala, Sreedevi Potluri, Chandra Srinivas Birke, Ali Hussen Mehra, Aashish Rajput, Sneha Padmavathi, Katakam Guru Nanak Institutions Technical Campus Department of Computer Science and Engineering Hyderabad India Werabe University Department of Information Technology Werabe Ethiopia Werabe University Department of Information Systems Werabe Ethiopia School of Retail Management Symbiosis University of Applied Sciences Indore India Prestige Institute of Management and Research Gwalior India Stanley College of Engineering and Technology for Women Department of Electronics and Communication Hyderabad India

ISBN: (纸本)9798350371055

This work presents and implements a low-cost irrigation system for smart agriculture that is based on the Internet of Things (IoT). In order to continuously monitor environmental data in real time, the system is equipped with a network of sensors, including pressure, temperature, moisture, and water level sensors. In order to anticipate when irrigation pumps will switch on, machine learning techniques including Artificial Neural Networks (ANN), Decision Trees (DT), Naive Bayes (NB), and Support Vector Machines (SVM) are linked depending on established parameters. The study shows that the ANN model can identify complicated patterns in the agricultural environment with an accuracy of up to 98.33%. Farmers are able to make well-informed decisions quickly thanks to the cloud connectivity and intuitive interface of remote monitoring and control. Because predictive modeling minimizes pump activation delays, it lessens the chance of both over- and under-irrigation. The suggested strategy makes the most use of available water and provides opportunities for precision farming, which is a major step forward for sustainable agriculture. The study's findings demonstrate how well the system uses resources and open the door for the future creation of innovative, scalable agricultural technology. © 2024 IEEE.

关键词： Agriculture IoT Machine Learning Precision Farming Water Management

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