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Application and research of GIS intelligent environmental protection Internet of things system construction technology

Application and research of GIS intelligent environmental pr...

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2019 international conference on Information Technology and computer Application, ITCA 2019

作者： Cheng, Yunli Zhao, Linling Guangzhou Nanyang Polytechnic College Guangzhou510925 China

ISBN: (纸本)9781728164946

the wisdom of this project is based on GIS environmental iot system building technical application and research, is the use of geographic space information technology, satellite remote sensing technology, global satellite positioning technology, radio frequency identification technology, based on the electronic map, image data, which is based on Internet, metropolitan area network, or LAN, in different spatial location of environmentally friendly iot devices intuitive visual control, intelligent identification, location and tracking, monitoring, alarm, inspection and maintenance of various environmental iot information flow, gathering and processing and statistical analysis, system management and comprehensive application of socialized service system. This project studies the application of the GIS based intelligent environmental protection Internet of things system platform with universal applicability, realizing the unified access, storage, exchange, analysis and application framework of environmental perception information, and establishing the data center of the platform. The system of "digital environmental protection" has been constructed, and the Internet of things and sensor network in the field of environmental protection have been gradually constructed to promote the transformation from "digital environmental protection" to "smart environmental protection" and "digital city" to "smart city", thus revolutionizing the improvement of urban management level. © 2019 IEEE.

关键词： Geographic information systems

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Research on Key Technologies of intelligent Fire Fighting Robot based on ZigBee Network

Research on Key Technologies of Intelligent Fire Fighting Ro...

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Artificial Intelligence and computer Engineering (ICAICE), international conference on

作者： Qi LIU Ye ZHANG Ying WANG Baohua LI Yao GOU Jiaojiao XU Deqing SHENG Zhuang LIU Jilin Institute of Chemical Technology College of information and control engineering JI Lin China

ISBN: (数字)9781728191461

ISBN: (纸本)9781728191478

At present, the existing fire extinguisher robots in China are generally unable to take into account the problems of autonomous movement, real-time monitoring and untimely extinguishing. In this paper, the intelligent fire-fighting robot based on Zigbee networks combined with Zigbee wireless sensor network technology, by building a network topological structure of the wireless sensor network (WSN), to acquire and transmit real-time robot's own position and the work area of environmental data, such as path finding independent planning to fire extinguishing work, effectively solve the fire-fighting robot problems such as save not in time, make the fire-fighting robot is widely used.

关键词： Wireless sensor networks Network topology Wireless networks Zigbee Robot sensing systems Real-time systems Robots

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intelligent monitoring and Regulation System of Crop Environment Based on Internet of Things 2

Intelligent Monitoring and Regulation System of Crop Environ...

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2nd IEEE international conference on Information Systems and computer Aided Education, ICISCAE 2019

作者： Ding, Yuechang Cao, Wenxu Gong, Yikun Li, Pan Lin, Zhenyou Southwest University of Science and Technology Information and Engineering Academy Mianyang China Southwest University of Science and Technology Economics and Management Academy Mianyang China

ISBN: (数字)9781728130668

ISBN: (纸本)9781728130668

The project uses a variety of technologies such as the Internet of Things and cloud platform to design a crop environment intelligent monitoring and adjustment system. The system can monitor multiple environmental indicators. When the environment is abnormal, the system can intelligently follow environmental parameters, control the adjustment strength of the equipment, and keep the growth environment in a favorable state. The cloud can connect multiple devices, with real-time monitoring, abnormal alarms, chart analysis and other functions to help better analyze the environment. This improves the traditional planting method, which requires a lot of labor and low efficiency, ensures the favorable environment of the crop, and improves the growth efficiency of the crop. © 2019 IEEE.

关键词： Crops

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Extending Lifetime of Wireless Sensor Network in Application to Road Traffic monitoring 26th

Extending Lifetime of Wireless Sensor Network in Application...

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26th international conference on computer Networks (CN)

作者： Lewandowski, Marcin Bernas, Marcin Loska, Piotr Szymala, Piotr Placzek, Bartlomiej Univ Silesia Inst Comp Sci Sosnowiec Poland Univ Bielsko Biala Bielsko Biala Poland Inst Innovat Technol EMAG Katowice Poland

ISBN: (纸本)9783030219529;9783030219512

The key issue in applications of wireless sensor networks is the limited lifetime of battery-powered sensor nodes. In this paper several methods were adapted and combined to extend the lifetime of the wireless sensor network. The considered network was designed for road traffic monitoring applications, such as detection of vehicles, bicycles, and pedestrians. Detailed experiments were conducted in order to determine lifetime of the sensor nodes in different real-world scenarios. The obtained results show that lifetime of the network for road traffic monitoring can be significantly extended by rotating the role of sensor nodes, suppressing unnecessary transmissions and putting the nodes to sleep mode according to a duty cycle.

关键词： Vehicle detection Pedestrian detection Sensor fusion Low-cost sensors intelligent transport systems

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APRON: an Architecture for Adaptive Task Planning of Internet of Things in Challenged Edge Networks 8

APRON: an Architecture for Adaptive Task Planning of Interne...

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8th IEEE international conference on Cloud Networking (CloudNet)

作者： Ventrella, Agnese V. Esposito, Flavio Sacco, Alessio Flocco, Matteo Marchetto, Guido Gururajan, Srikanth St Louis Univ St Louis MO 63103 USA Politecn Torino Turin Italy

ISBN: (数字)9781728148328

ISBN: (纸本)9781728148328

Recently, the growth of Internet of Things (IoT) devices combined with edge computing opened many opportunities for several novel applications. Typical examples are Unmanned Aerial Vehicles (UAV) that are deployed for photogrammetry, surveillance, disaster rapid response and environmental monitoring. A common challenge across all these networked applications is the ability to provide a persistent service - a service able to continuously maintain a high level of performance - responding to events that may change the state of the network, e:g:, nodes or link failures. To cope with this challenge, in this paper we propose APRON, an edge cloud-assisted architecture for distributed and adaptive task planning management in a network of IoT devices, e:g:, drones. APRON uses a novel planning strategy that, leveraging a Jackson's network model, supports monitoring and control operations while the states of the (edge or cloud) network evolve. By using APRON, edge computing application programmers can design and implement a wide range of IoT task management policies leveraging different protection methodologies across several failure models.

关键词： Task analysis Drones Planning computer architecture monitoring Steady-state Adaptive systems

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User authentication scheme for greenhouse remote monitoring system using WSNs/IOT 19

User authentication scheme for greenhouse remote monitoring ...

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3rd international conference on Future Networks and distributed Systems, ICFNDS 2019

作者： Akhtar, Muhammad Hussain, Majid Arshad, Jehangir Ahmad, Mudassar Department of Computer Science Comsats University Islamabad Pakistan Department of Electrical Engineering Comsats University Islamabad Pakistan National Textile University Faisalabad Pakistan

ISBN: (纸本)9781450371636

Use of modern machinery and technology has significantly reduced the labor work in agriculture. The next level was to make growth of vegetables/ crops independent of seasons. This was made possible by introducing greenhouses. Essence of greenhouse lies in control of environmental parameters like temperature, humidity, light, pressure and CO 2 as per specific crop needs. Integrating IOT technology with greenhouse enables us to remotely monitor the greenhouse environment and control its parameters intelligently. OT and WSNs deployed in greenhouse require a secure and efficient connectivity with monitoring/ control room. While deploying a WSN for greenhouse following aspects are worth considering. Hardware Connectivity User Authentication The objective of this research is to devise a user authentication scheme for deployment of IOT in greenhouse environment. © 2019 Association for Computing Machinery.

关键词： Authentication

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intelligent DDoS Detection System in Software-Defined Networking (SDN)

Intelligent DDoS Detection System in Software-Defined Networ...

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IEEE international conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Chaitanya Kumar Bathini Pranay Kumar Aditya Chaudhary Ayush Gupta Kapil Dev Ayushi Sharma Shashank Srivastava Rajitha B. Motilal Nehru National Institute of Technology Allahabad Prayagraj India

ISBN: (数字)9781728168289

ISBN: (纸本)9781728168296

Software defined network (SDN) is a network paradigm that decouples the control and data plane of network layer by introducing a logically centralized control known as controller. SDN promises network monitoring, easy and instant network implementation and effective central control but at the same time this central control introduces a single point of failure thereby increasing the risk of distributed Denial of Service (DDoS) attacks. Thus, this paper analyses the various types of DDoS attacks that can be performed in SDN environment with the help of various attack models. Further, an attempt is made to analyze such attacks and bring out the features that could uniquely classify legitimate traffic and attack traffic using machine learning techniques. Finally, an Open Network Operating System (ONOS) controller module is developed that could live detect any ongoing DDoS attack.

关键词： computer crime Entropy Feature extraction Switches Protocols IP networks

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Combined approach to forecasting of manufacturing system target indicators in a changing external environment 23rd

Combined approach to forecasting of manufacturing system tar...

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23rd KES international conference on Knowledge-Based and intelligent Information and Engineering Systems (KES)

作者： Avdeeva, Zinaida Grebenyuk, Elena Kovriga, Svetlana Trapeznikovs Inst Control Sci RAS Profsouznaya St 65 Moscow 117997 Russia

The paper presents a combined approach to forecasting of the manufacturing system target indicators, depending on the key factors determining the functioning of this system and business environmental factors. The approach includes: (i) identification of key factors and weak signals influencing the target indicators by analyzing the system functioning model in the external environment represented by a cognitive map of the situation;(ii) analysis of dynamics of the identified key factors and manufacturing system target indicators and the construction of a forecast model using time series analysis methods;(iii) monitoring of the heterogeneous information space in order to detect changes in trends and the composition of parameters of the forecast model;(iv) correction of the forecast model and cognitive map of the situation according to the results of the detected changes. The approach is focused on the formation of long-term forecasts of the target indicators and increasing the accuracy of these forecasts by identifying significant influencing events whose influence does not have time to reflect in time series. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： manufacturing system target indicators forecasting cognitive map time series monitoring

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12th international conference on intelligent Robotics and Applications, ICIRA 2019

12th International Conference on Intelligent Robotics and Ap...

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12th international conference on intelligent Robotics and Applications, ICIRA 2019

ISBN: (纸本)9783030275402

The proceedings contain 378 papers. The special focus in this conference is on intelligent Robotics and Applications. The topics include: intelligent Robot Arm: Vision-Based Dynamic Measurement System for Industrial Applications;research on Autonomous Face Recognition System for Spatial Human-Robotic Interaction Based on Deep Learning;KPCA-Based Visual Fault Diagnosis for Nonlinear Industrial Process;data Denosing Processing of the Operating State of the Robotic Arm of Coal Sampling Robot;a Study on Step-by-Step Calibration of Robot Based on Multi-vision Measurement;characteristic Frequency Input Neural Network for Inertia Identification of Tumbling Space Target;An FFT-based Method for Analysis, Modeling and Identification of Kinematic Error in Harmonic Drives;real-Time Human-Posture Recognition for Human-Drone Interaction Using Monocular Vision;HSVM-Based Human Activity Recognition Using Smartphones;stability Analysis and Fixed Radius Turning Planning of Hexapod Robot;Human-AGV Interaction: Real-Time Gesture Detection Using Deep Learning;Coverage Path Planning for Complex Structures Inspection Using Unmanned Aerial Vehicle (UAV);development of Four Rotor Fire Extinguishing System for Synchronized monitoring of Air and Ground for Fire Fighting;A Small Envelope Gait control Algorithm Based on FTL Method for Snake-Like Pipe Robot;trajectory Tracking control of Wheeled Mobile Robots Using Backstepping;the Design of Inspection Robot Navigation Systems Based on distributed Vision;mobile Robot Autonomous Navigation and Dynamic environmental Adaptation in Large-Scale Outdoor Scenes;movement Analysis of Rotating-Finger Cable Inspection Robot;autonomous Indoor Mobile Robot Exploration Based on Wavefront Algorithm;multi-robot Path Planning for Complete Coverage with Genetic Algorithms;the Mechanical Design and Torque control for the Ankle Exoskeleton During Human Walking.

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Visual classification of lettuce growth stage based on morphological attributes using unsupervised machine learning models

Visual classification of lettuce growth stage based on morph...

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2020 IEEE Region 10 conference, TENCON 2020

作者： Alejandrino, Jonnel Concepcion, Ronnie Lauguico, Sandy Tobias, Rogelio Ruzcko Almero, Vincent Jan Puno, John Carlo Bandala, Argel Dadios, Elmer Flores, Ramon De la Salle University-Manila Laguna State Polytechnic University-SCC Electronics Engineering Manila Philippines De la Salle University Electronics and Communications Engineering Department Manila Philippines De la Salle University Electronics Communications Engineering Department Manila Philippines De la Salle Universit Manufacturing Engineering and Management Department Manila Philippines Laguna State Polytechnic University Electronics Communications Engineering Department Manila Philippines

ISBN: (纸本)9781728184555

Food shortage is a serious problem facing the world and is prevalent in urban areas. The scarcity of food is mainly caused by crop failure. environmental factors offered by the rural areas determine the condition of crops to be produced. This scenario pomps, the explication of urban farming. However, urban farming requires all-out monitoring and control. This study specifically solves the predicament of identifying the developmental growth of plants from seed leaf to amend the techniques of plant science and cultivation management. With a view to this, the paper shows coupled color-based superpixels and multifold watershed transformation in segmenting the lettuce image from the background. To fathom it out, a comparative analysis of three unsupervised machine learning algorithms: Self Organizing Map (SOM), Hierarchical, and K - means algorithms were conducted. These were done by modeling each algorithm from the features extracted from morphological computations of the lettuce images raised in a smart aquaponics setup. Each of the models was optimized to increase cross and hold-out validations. The results showed that K - means algorithm having the parameters of algorithm = 'auto', copyx= 'True', init = 'K- means++', maxiter = '1000', nclusters = '3', ninit = '15', n-jobs = '1', precompute-distance = 'auto', random-state = '10', tol = '0.000001', verbose = '1', leaf-size = '10' was the most effective model for the given dataset, yielding a high precision and recall unsupervised clustering percentage of 91%. © 2020 IEEE.

关键词： computer vision

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