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Development of new technologies for real-time traffic monitoring

AIP conference Proceedings 2022年第1期2681卷

作者： Abdulaziz Ayedh A Aldakkhelallah Nirajan Shiwakoti Tom Dabic Justin Lu Winston Yii Milan Simic 1School of Engineering RMIT University Melbourne Australia 2Real Time Traffic Pty Ltd 7/17-21 Barretta Rd Ravenhall VIC 3023 Australia

Research and innovations in intelligent Transport Systems (ITS) bring numerous benefits to local and global communities. ITS is defined as a system based on the application of contemporary computer and communication technologies into transport, to increase traffic efficiency, reduce pollution and other environmental effects of transport, and increase travelers’ safety. The main goals of our research, reported here, are to improve the safety and efficiency of transport. We investigate a comprehensive solution that includes computer vision, Internet of Things (IoT), social media and AI control of the whole transport system. Autonomous vehicles and vehicular ad hoc networks are intelligent subsystems that will also be integral parts of future transport systems. This is expected to significantly improve traffic safety and throughput which will deliver sustainable economic and environmental benefits to the industry and the community. In alignment with vision zero approaches, we aim at zero human casualties on the road and fewer greenhouse gases emissions. Road transport safety is a critical topic of state, national and international importance, due to the health and safety of the community and serious environmental implications. Public opinion is extremely important in the changes to come and we are presenting here results from a survey that we have conducted.

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Secured remote control of greenhouse based on wireless sensor network and multi agent systems

Secured remote control of greenhouse based on wireless senso...

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international conference on Advanced intelligent Systems for Sustainable Development, AI2SD 2018

作者： Moummadi, Kamal Abidar, Rachida Medromi, Hicham Ziani, Ahmed Hassan II University ENSEM BP 8118 Oasis Casablanca Morocco

ISBN: (纸本)9783030120641

QueryAgent-oriented formalisms are now increasingly used in artificial intelligence. Their success is partly due to their easy adaptation to the needs of distributed real-time applications. This paper explains the design and implementation of a novel platform called Secured Remote control of Greenhouse (SRCG) for the remote control of the inside and outside climatic and also soil parameters that influence the production in greenhouses such as temperature, humidity, CO2 and soil moisture…. A Wireless Sensor Network (WSN) provides pertinent information that is used to supervise ventilation, heating and pump…. The use of SRCG avoids the needed to perform the monitoring actions on site. The platform described in this paper is simple to be installed and used by farmers who do not have knowledge in computer skills. Thus, all farmers can control their greenhouses from a distance device in an easy and an ubiquitous manner. They can control actuators to adjust these parameters (fan, heater, drip irrigation…). The architecture of the platform is based on Multi agent systems (MAS) and a distributed Constraint Satisfaction Problem (DCSP). MAS gather, integrate, and deliver the collected climate’s parameter information from distributed sensors, and synchronize this information with a remote supervisor computer. Proposed SRCG has advantage that can handle situations in the far away area from the farms through PDA (Personal Digital Assistant) and mobile device, which shortens time, expense and supports agricultural decision-making. The prototype is built in Java employing general interfaces of both MAS and constraint programming (CP) platforms, using JADE and CHOCO libraries. © Springer Nature Switzerland AG 2019.

关键词： Greenhouses

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A multidimensional human-centric framework for environmental intelligence: Air pollution and noise in smart cities

A multidimensional human-centric framework for environmental...

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international conference on distributed Computing in Sensor Systems (DCOSS)

作者： Andreas Bardoutsos Gabriel Filios Ioannis Katsidimas Thomas Krousarlis Sotiris Nikoletseas Pantelis Tzamalis Computer Engineering and Informatics Department University of Patras Patras Greece Inlecom Innovation Athens Greece

ISBN: (数字)9781728143514

ISBN: (纸本)9781728198040

For the important problem of increasing levels of air pollution and noise in urban and rural areas, we propose a holistic, multi-dimensional approach to gather, monitor and analyze heterogeneous data sources of air pollutants and noise indicators, into an integrated, intelligent computational system. Although several interesting approaches have been developed for monitoring pollution and noise, however the challenge remains for even more detailed, precise, large scale *** overcome the limitations of current systems, we envision an integrated approach to human-centric environmental intelligence, bringing together modern IoT technology and the human factor. In particular, our approach emphasizes selected behavioural and health aspects, and the complementary use of sensing technology with citizen engagement and crowdsourcing methods. The proposed system will collect diverse data from heterogeneous sources, such as mobile and static wireless sensor networks, crowdsourcing, citizen questionnaires and social media analytics, to continuously combine objective estimations with subjective perception of air quality and noise. With the use of advanced AI and Deep Learning algorithms, our system will be able to estimate air pollutants concentration and noise levels in micro-scale with adequate precision over large urban-scale environments. Furthermore, tracking of behavioral and psychological users' input, as well as personal exposure to pollution, will allow studying the impact of air quality and noise on the users' daily habits and the interplay of ambient conditions with behavioural factors, towards an active engagement of citizens in a hybrid techno-social manner. A reference architecture for the realization of this human-centric environmental intelligence approach is presented. Also, a planned implementation at the city of Patras, Greece is discussed. To the best of our knowledge, this is one of the first holistic, multifaceted approaches to a surveillance system

关键词： Air pollution monitoring Urban areas Sensors Wireless sensor networks

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distributed Hierarchical Fault Diagnosis Based on Sparse Auto-Encoder and Random Forest 4th

Distributed Hierarchical Fault Diagnosis Based on Sparse Aut...

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4th international conference on Machine Learning and intelligent Communications, MLICOM 2019

作者： Li, Tong Song, Chunhe Liu, Yang Wang, Zhongfeng Yu, Shimao Su, Shanting Liaoning Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. 110000 Shenyang China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9783030323875

For the diagnosis of large-scale local devices, the traditional centralized fault diagnosis systems are becoming incompetent to meet the requirement of real-time monitoring. This paper proposes the distributed hierarchical Fault Diagnosis System (DFDS). Specifically, DFDS implements fault monitoring by an improved Sparse Auto-Encoder (SAE) on the monitor layer, classifies faults and identifies unknown faults by an improved random forest on the classification layer, learns new knowledge and updates the system on the decision layer. We apply DFDS in the laboratory data of Case Western Reserve University to verify the efficiency of the proposed system. The experimental results show that our method can accurately detect the fault and accurately identify the fault type. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Fault detection

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Security measures in distributed approach of cloud computing

Security measures in distributed approach of cloud computing

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international conference on Cognitive Informatics and Soft Computing, CISC 2017

作者： Shirisha Reddy, K. Bala Raju, M. Naik, Ramana Department of Computer Science and Engineering JNT University Kukatpally HyderabadTelangana500085 India Department of Computer Science and Engineering KITE JNT University Kukatpally HyderabadTelangana500085 India Department of Computer Science and Engineering Farah Engineering College Chevella HyderabadTelangana501503 India

ISBN: (纸本)9789811306167

Cloud computing has given a new approach of data accessing in a distributed manner, where the users has the advantage of higher data accessing feasibility. This approach works on the approach of outsourcing the storage requirements in public provider. The distributed approach has the advantage of low cost data accessing, scalable, location independent and reliable data management. It is observed that Conventional approaches are focused to achieve the objective of reliable and secure data access in cloud computing. However the signaling overhead in these approaches was not explored: in the exchange of control signal in cloud computing, it is needed that lower effort should be made for authentication and data integrity, so as more accessing provision exists. A new monitoring scheme is proposed to minimize the signaling overhead by monitoring record systems. In this paper, security issues also focused. In this process, at each of the data exchange, security risk arises, which are evaluated by different security measure such as Mean failure cost (MFC), and multi-dimensional failure cost (M2FC). To demonstrate our approach, To develop the suggested objectives, MATLAB interfacing with data feed toolbox was used, effectiveness of the proposed method has been shown by the experimental results. © 2019, Springer Nature Singapore Pte Ltd.

关键词： MATLAB

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intelligent joint trajectory design and resource allocation in UAV-based data harvesting system

Intelligent joint trajectory design and resource allocation ...

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international conference on control and Automation (ICCA)

作者： Siyu Luo Junkai Liu Siyu Chen Jienan Chen Jifeng Guo Artificial Intelligence Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

With the development of Internet of Things (IoT) technology, wireless sensor networks (WSNs) composed of multiple sensor nodes (SNs) have been able to provide a large number of high-quality services, such as continuous environmental monitoring, automatic control, and transmission of data for intelligent decision-making. SNs in WSNs are typically energy limited and often exist in large numbers, which are widely distributed in hard-to-reach areas. Hence, it is difficult to collect data from SNs without infrastructure support such as base stations (BSs). The low cost and high maneuverability of unmanned aerial vehicles (UAVs) provide an efficient solution for data acquisition in WSNs but with the challenge of control system of the UAV. In this paper, we proposed a deep reinforcement learning based UAV control system to intelligently solve the data harvesting problem in WSNs. Our optimization target is to jointly optimize the trajectory of the UAV and the bandwidth resources of the airborne base station to maximize the data acquisition success rate when the UAV is limited in energy. The objective function and constraints of this problem are highly non-convex. To solve this problem, we first modeled the movement of the UAV and the bandwidth allocation of the airborne base station in each time slot as a Markov decision process (MDP). Then we designed a deep reinforcement learning architecture to solve the above MDP. Compared with the existing data harvesting algorithms, the proposed method has a great improvement in data acquisition success rate.

关键词： Unmanned aerial vehicles Trajectory Wireless sensor networks Bandwidth Schedules Data acquisition Fading channels

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Video monitoring System Application to Urban Traffic Intersection 11th

Video Monitoring System Application to Urban Traffic Interse...

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11th EAI international conference on Simulation Tools and Techniques, SIMUTools 2019

作者： Sun, Jin-ping Chen, Lei Bao, Rong Li, Dan Jiang, Dai-hong Key Laboratory of Intelligent Industrial Control Technology of Jiangsu Province Xuzhou University of Technology XuzhouJiangsu221000 China

ISBN: (纸本)9783030322151

intelligent video surveillance technology can reduce the burden of workers and improve the efficiency of surveillance. A project of the video monitoring system with moving target detection function has been realized and applied to the urban traffic system. The background will have weak or obvious changes as time goes on, such as, the illumination change, the environmental effect, the movement of the background, and so on. If we always use the original background model, it will cause large error. Fixed threshold is not suitable for illumination change in the environment. An improved adaptive on-line Gauss mixture model is used to acquire the background model, and the background subtraction method is used to match the moving objects. Then, the motion detection function was realized in a specific region. If there are abnormal moving targets in a specific area, the linkage alarm function will be activated and handled by manual intervention. This algorithm can effectively reduce the error probability of target recognition caused by environmental changes, and provide strong technical support for real-time monitoring of traffic abnormalities. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2019.

关键词： Mixtures

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Predictive Maintenance of Air Conditioning Systems Using Supervised Machine Learning 20

Predictive Maintenance of Air Conditioning Systems Using Sup...

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20th international conference on intelligent System Application to Power Systems, ISAP 2019

作者： Trivedi, Shrishti Bhola, Sahil Talegaonkar, Archit Gaur, Prerna Sharma, Shreya Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India Computer Science Engineering Indraprastha Institute of Information Technology New Delhi India

ISBN: (纸本)9781728131924

Various types of faults can occur in an air conditioner resulting in a decrease in efficiency, a rise in energy consumption, and increasing maintenance costs. Hence predictive maintenance becomes important. In this paper, the two most common types of faults - gas leakage and capacitor malfunction have been detected using the decision tree machine learning algorithm. The data for faulty and operating air conditioners have been collected using distributed sensors, microcontroller, and dedicated circuitry and analyzed using MATLAB Classification App Learner Toolbox. The results obtained by the decision tree for fault detection and diagnosis and load monitoring were then compared with results obtained by support vector machine and the prediction accuracy for the decision tree was found to be higher. The presented research work can identify the air conditioner which is faulty as well as predicts the type of fault at an early stage to do maintenance beforehand. © 2019 IEEE.

关键词： Air conditioning

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Multi-functional Smart Car Based on Wireless Communication Technology

Multi-functional Smart Car Based on Wireless Communication T...

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IEEE international conference on Mechatronics and Automation

作者： Junchao Zhu Huifeng Cao Baofeng Zhang Yunlong Xing Chang Jia Engineering Research Center of Optoelectronic Devices & Communication Technology Ministry of Education China Binshui Xidao 391 Tianjin China Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin University of Technology Binshui Xidao 391 Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

In view of the high risk of working in the complex unknown environment, the intelligent car is used to monitor the concentration, temperature and humidity of harmful gases in the environment, collect the actual geographical information of the unknown environment and other functions. In this paper, through upper and lower computer control scheme, the smart car based on wireless communication technology is researched, components including main-control chip based on ATmega328P single-chip microcomputer (SCM), AR9331 wireless transmission chip, and various sensors are selected to construct the whole system, functions like screen image acquisition and passing back, and monitoring environmental gas concentration and humiture are realized. The result indicates, the system of multi-functional smart car based on wireless communication technology is stable enough to meet practical demand.

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An Integrated UAV Platform for Real-Time and Efficient environmental monitoring 14th

An Integrated UAV Platform for Real-Time and Efficient Envir...

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14th international conference on Wireless Algorithms, Systems, and Applications (WASA)

作者： Xu, Linyan Fu, Zhangjie Ma, Liran Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing Peoples R China Texas Christian Univ Dept Comp Sci Ft Worth TX 76129 USA

ISBN: (纸本)9783030235970;9783030235963

An important part of environmental monitoring is the collection of meteorological data. In this paper, we develop an integrated data acquisition and transmission platform utilizing unmanned aerial vehicles (UAVs) with an intelligent path planning algorithm to achieve efficient and accurate meteorological data collection in real-time. We adopt the improved traveling salesman problem model to represent the path planning problem. Based on the model, we propose an improved simulated annealing genetic algorithm (ISAGA) to solve the path planning problem. Our proposed ISAGA is able to overcome the deficiencies of the traditional genetic algorithm and simulated annealing algorithm. In addition, we design and implement a mobile application integrated with the path planning algorithm to control UAVs and conduct data exchange to the cloud. Our evaluation results demonstrate that data can be collected and transmitted more efficiently via selecting better paths.

关键词： environmental monitoring UAV path planning Genetic algorithms

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