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IoT-Driven Smart Irrigation for Paddy Cultivation using BCO-ResNet: A Deep Learning Approach

IoT-Driven Smart Irrigation for Paddy Cultivation using BCO-...

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Electronics and Renewable Systems (ICEARS), international conference on

作者： R. Anbarasu V. Parthipan Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Science Thandalam Tamil Nadu India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Raising crop yield and simultaneously addressing the worldwide water shortage issue depends on good water management in paddy farming. Considered conventional irrigation methods often waste water, cause poor monitoring, and produce insufficient crops. Deep learning and the Internet of Things (IoT) taken together offer a transforming solution that greatly improves real-time monitoring and decision-making in agriculture. This work attempts to introduce a special Bee Colony Optimisation (BCO)-ResNet model designed for paddy fields, so addressing intelligent irrigation systems. Soil moisture, temperature, humidity, and water level data is gathered using Internet of Things sensors. Proposed then, the BCO-ResNet model addresses this information. Although BCO is in charge of simplifying the feature selection process, the ResNet architecture guarantees accurate classification and irrigation demand prediction. One can considerably cut water waste by means of dynamic control of water distribution in the system. Ten paddy fields gathered over a six-month farming period made up a dataset used to test the model's efficiency. In irrigation accuracy of 95.6%, water use efficiency improvement of 38%, and crop yield increase of 22%, the proposed system exceeded traditional methods. Moreover, 18% of the time required for real-time decision making was shortened, which fits usage in environments with limited resources. These findings indicate that the BCO-ResNet model maximises irrigation for paddy fields, so supporting the expansion of economically sustainable agriculture. Applying this system to many various crops and environmental conditions has the potential to change the way water management techniques are applied in agricultural environments.

关键词： Support vector machines Deep learning Temperature sensors Irrigation Accuracy Decision making Real-time systems Internet of Things Water resources Farming

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Fuzzy Dynamic Centrality for Urban Traffic Resilience

Fuzzy Dynamic Centrality for Urban Traffic Resilience

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2021 international conference on Data Analytics for Business and Industry, ICDABI 2021

作者： Badaoui, Fatima-Ezzahra Boulmakoul, Azedine Thami, Rachid Oulad Haj Hassan Ii University of Casablanca Computer Sc. Dept Fstm Mohammedia Morocco Mohamed v University Admir Lab Ensias Rabat Morocco

ISBN: (纸本)9781665416566

When traveling to and from home, work or vacation, we have all experienced traffic delays. As a result, road travelers often add time to their trip in advance to anticipate traffic jams. Meanwhile, unplanned traffic jams can be fundamentally problematic for travelers. Which are caused by a variety of reasons, such as road closures, events, or severe weather. In this study, we shed the light on the importance of travel time in the detection of traffic congestion. We propose a fuzzy process to measure the uncertainty in the computation of travel time in order to develop fuzzy dynamic centrality for the detection of traffic congestion. A simulation is conducted on a small area from Mohammedia city using microscopic traffic simulator SUMO'. The calculation of the uncertainty of the estimated travel time over the study period is based on the generation of Gaussian fuzzy numbers. Our proposed study is an essential component of smart traffic monitoring and provides genuine assistance for urban network resilience. © 2021 IEEE.

关键词： Traffic congestion

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Vehicle information collection and communication system based on CAN bus and GPS

Vehicle information collection and communication system base...

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2021 international conference on computer Technology and Power Electronics, ICCTPE 2021

作者： Liu, Li Liu, Wei Peng, Kaiqin Wuhan Railway Vocational CoIIege of Technology WuHan430205 China Hubei institute of water resources survey and design WuHan430064 China

With the proportion of automobile industry in people's work and life increasing year by year, the automotive intelligent terminal market has ushered in a huge development prospect. On-board information system is a set of control system used to collect, store and display all kinds of information status in the process of automobile running. controller Area Network (CAN) is a serial communication field bus network that effectively supports distributed monitoring or real-time control. Through the CAN bus technology, the vehicle-mounted intelligent terminal can easily interact with other devices in the automobile, so as to master the running status of the vehicle. The vehicle-mounted 3D acquisition system continuously acquires the traveling position of the measuring vehicle through GPS, and provides geographic coordinates for the 3D spatial images acquired by the measuring vehicle, thus realizing the 3D scene with spatial geographic coordinates. Relying on CAN bus and GPS technology, the vehicle-mounted intelligent terminal can conveniently obtain the surrounding road condition information and send its own vehicle data to the remote control center. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Real time control

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Design of intelligent Safety Protection Robot Based on Global Position System and Machine Vision 2

Design of Intelligent Safety Protection Robot Based on Globa...

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2021 2nd international conference on computer Information and Big Data Applications, CIBDA 2021

作者： Ming, Yang Yufei, Li Wuhan Technology and Business University Wuhan Hubei430000 China Chang Jiang Institute of Survey Planning Design and Research Wuhan Hubei430000 China

In this paper, an intelligent safety protection robot based on the integration of Global Position System(GPS) and machine vision is designed. The robot takes STM32F407 as the control core and is equipped with a variety of environmental monitoring sensors to realize real-time monitoring of the surrounding environment and alarm for potential safety hazards. In order to realize the stable and accurate autonomous navigation of robot, a system combining GPS technology with visual simultaneous localization and mapping (V-SLAM) technology is designed. GPS module collects longitude and latitude information, driving speed and heading Angle to complete the absolute positioning of the robot. Machine vision device collects image information, and the relative positioning of the robot is completed through digital image processing technology. The two positioning information was fused and output new positions and postures through Unscented Kalman Filter (UKF). Through the experimental verification of the combined navigation and positioning effect, the GPS and machine vision integrated navigation device has high precision, and the maximum error is controlled within 0.1 meters. © Published under licence by IOP Publishing Ltd.

关键词： computer vision

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7th international conference on Technologies and Innovation, CITI 2021

7th International Conference on Technologies and Innovation,...

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7th international conference on Technologies and Innovation, CITI 2021

ISBN: (纸本)9783030882617

The proceedings contain 14 papers. The special focus in this conference is on Technologies and Innovation. The topics include: Preface;approach Based on Text Processing and Ontology Applied to the Health Domain of Palliative Care in Panama;relationships of Compression Ratio and Error in Trajectory Simplification Algorithms;sensor Network Prototypes for environmental Noise monitoring Based on Free Software;agrotechnology: Analysis of the Services Offered by Mobile Applications for the Agronomic control of Orchards;automation of Poultry Production monitoring Through Web Services;A Brief Systematic Review of the Latest Advances in IOT Platforms in Agriculture;data Governance, a Knowledge Model Through Ontologies;on intelligent Fingerprinting of Antique Buildings from Clay Composition;emotional Corpus, Feature Extraction and Emotion Classification Using the Parameterized Voice Signal;importance of international R&D Collaboration Between Companies: The CollaborativeHealth Use Case;evaluating Extractive Automatic Text Summarization Techniques in Spanish.

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Biomonitoring Technologies Used in Aquatic Ecosystems: A Systematic and Trend Analysis 14

Biomonitoring Technologies Used in Aquatic Ecosystems: A Sys...

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14th IEEE international conference on Humanoid, Nanotechnology, Information Technology, Communication and control, Environment, and Management, HNICEM 2022

作者： Arroyo, Carey Louise Dionela, Matthew Ann Bautista, Mary Grace Concepcion, Ronnie Vicerra, Ryan Rhay Duarte, Bernardo De la Salle University Department of Manufacturing Engineering and Management Manila Philippines De la Salle University Department of Electronics and Computer Engineering Manila Philippines Faculdade de Ciências da Universidade de Lisboa MARE - Marine and Environmental Sciences Centre ARNET - Aquatic Research Infrastructure Network Laboratory Campo Grande Lisbon1749-016 Portugal Universidade de Lisboa Faculdade de Ciências Departamento de Biologia Vegetal Lisbon Portugal

ISBN: (纸本)9781665464932

Aquatic biomonitoring technologies are widely used to detect and identify hazardous chemicals and pollutants in aquatic ecosystems. With the advancement of technology, this study focuses on providing a review of current trends and challenges related to aquatic biomonitoring. In particular, the advancements made in the designs of biosensors and Biological Early Warning Systems (BEWS) were presented. This includes biosensors that utilize luminescent bacteria, algae, living and/or microbial fuel cells. For BEWS, those that use fishes, daphnids, and bivalves as sentinel organisms were discussed. It was shown that biosensors and BEWS show promising potential for monitoring water quality of aquatic ecosystems as they allow for real-time monitoring while performing comparably to traditional analytical methods. Despite the various research done, there are still some issues and challenges concerning aquatic biomonitoring. BEWS and biosensors were shown to have their advantages and disadvantages. Biosensors can quantify the tested parameters but are analyte-specific and often need to be replaced upon detection. On the other hand, BEWS allow for continuous real-time monitoring but are often site-specific and require an established baseline data of the water quality parameters. To combat the issues, this study proposes designing a BEWS using bivalves for early detection and utilizing analytical methods to confirm changes in water quality. It is also recommended that further research be done to determine levels of toxicity, capacity to meet needs, and water quality baseline data for local aquatic ecosystems. © 2022 IEEE.

关键词： Water quality

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

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

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international conference on Smart Technologies For Smart Nation (SmartTechCon)

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

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.

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Real-Time Anomaly Detection in 5G Networks Through Edge Computing

Real-Time Anomaly Detection in 5G Networks Through Edge Comp...

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IEEE international conference on intelligent Techniques in control, Optimization and Signal Processing (INCOS)

作者： Riaz Shaik Dara Raju Prakash Chandra Behera Ravindra Changala S. Suma Christal Mary A. Balakumar Department of CSE KL University Vaddeswaram Andhra Pradesh India Dept. of Computer Science & Engineering Vignana Bharathi Institute and Technology Aushapur Ghatkesar India Department of Science St. Claret College Bangalore India Department of Information Technology Guru Nanak Institutions Technical Campus Hyderabad India Department of Information Technology Panimalar Engineering College Poonamalle Chennai Department of ECE K. Ramakrishnan College Of Engineering samayapuram Trichy India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Strong anomaly detection techniques are becoming more and more necessary as 5G networks develop in order to maintain network performance, security, and dependability. This study leverages the capabilities of Mobile Edge Computing (MEC) to present a novel method for anomaly detection in 5G networks. By processing data closer to the network edge, the integration of MEC offers an efficient and decentralized architecture that lowers latency and improves real-time detection capabilities. The distributed module takes advantage of its close proximity to network devices by using sophisticated algorithms for anomaly detection, which are implemented at the mobile edge. The system can quickly detect abnormalities from typical network activity by utilizing capabilities including Flow Collection, Anomaly Symptom Detection, and Network Anomaly Detection. The distributed module provides anomalous information to the centralized decision-making module for thorough examination. It takes into account variables like resource use and network traffic and integrates this data with metrics gathered from monitoring modules. Because of its adaptive characteristics, the system may expand anomaly detection components, enhance detection functions, and modify virtualized resources in response to shifting network circumstances. The evaluation findings reveal that the suggested anomaly detection method performs well in 5G networks, with decreased false positives, increased responsiveness, and better flexibility to changing network conditions. Using MEC not only makes anomaly detection more effective, but it also fits in with the 5G design, which makes it a viable option for protecting the upcoming generation of communication networks. It obtains 95% accuracy in classification. The suggested approach has proven to be resilient in handling security issues by producing outcomes that are either comparable to or better than those attained by other techniques that have been previously presented in the s

关键词： Multi-access edge computing 5G mobile communication Image edge detection Signal processing algorithms Telecommunication traffic Signal processing Real-time systems

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Research on virtual human swarm football collaboration technology based on reinforcement learning

Research on virtual human swarm football collaboration techn...

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IEEE international Symposium on Parallel and distributed Processing with Applications and IEEE international conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Xiaoshan Mo Bin Hu Caixu Xu Yuling Yang Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China Faculty of Arts and Humanities Macao University of Science and Technology Macao China

Reinforcement learning is used in many applications in artificial intelligence fields such as computer vision and environmental contextualized decision-making scenarios; virtual human swarms provide research directions for multi-intelligent body collaboration and environmental field detection in multi-intelligent body swarms. Football is a group sport, which is characterized by its holistic nature, confrontation, versatility, and ease of implementation, as well as the characteristics of both individual intelligence and group intelligence, and is a typical application scenario for multi-intelligence collaboration. This paper takes football as the research object to study the team collaboration problem and team gaming problem of the virtual human swarm in a specific environment and solves the cooperation and competition relationship between intelligence with reinforcement learning of multi-intelligence training.

关键词： Training computer vision Decision making Collaboration Reinforcement learning Ubiquitous computing Artificial intelligence

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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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international Russian Automation conference (RusAutoCon)

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

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

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.

关键词： Smart cities Scalability Transportation Switches Routing Blockchains Consensus protocol Security Usability Optimization

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