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Raspberry Pi as visual sensor Nodes in Precision Agriculture: A Study

IEEE ACCESS 2019年 7卷 45110-45122页

作者： Kamath, Radhika Balachandra, Mamatha Prabhu, Srikanth Manipal Acad Higher Educ Manipal Inst Technol Dept Comp Sci Manipal 576104 Karnataka India

wireless sensor network applications in the agricultural sector are gaining popularity with the advancement of the Internet of Things technology. Predominantly, wireless sensor networks are used in agriculture to sense the important agricultural field parameters, such as temperature, humidity, soil moisture level, nitrite content in the soil, groundwater quality, and so on. These sensed parameters will be sent to a remote station, where it will be processed and analyzed to build a decision support system. This paper describes the implementation of a wireless visual sensor network for precision agriculture to monitor paddy crop for weeds using Raspberry Pi. Bluetooth 4.0 was used by visual sensor nodes to send the data to the base station. Base station forwarded the data to the remote station using IEEE 802.11 a/b/g/n standard. The solar cell battery was used to power up the sensor nodes and the base station. At the remote station, images were preprocessed to remove soil background and different shape features were extracted. Random forest and support vector machine classifiers were used to classify the paddy crop and weed based on the shape features. The results and observations obtained from the experimental setup of the system in a small paddy field are also reported. This system could be expected to enhance the crop production by giving timely advice to the crop producers about the presence of weeds so that steps can be taken to eradicate weeds.

关键词： Classifiers computer vision precision agriculture Raspberry Pi 3 model B shape features wireless visual sensor network

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3-D Application-Oriented visual Correlation Model in wireless Multimedia sensor networks

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IEEE sensorS JOURNAL 2017年第8期17卷 2583-2595页

作者： Yang, Xiaotao Wen, Yingyou Yuan, Duoning Zhang, Mingyang Zhao, Hong Northeastern Univ Sch Comp Sci & Engn Shenyang 110819 Peoples R China Neusoft Corp State Key Lab Software Architecture Shenyang 110179 Peoples R China Northeastern Univ Sch Business Adm Shenyang 110819 Peoples R China

wireless multimedia sensor networks comprise a large number of sensor devices and obtain multiple types data from field of interest. In a visual sensor network, there exist visual correlation (VC) characteristics among images observed by camera-equipped sensors with overlapped field of views. To describe the characteristics, the conventional method is based on image matching. However, it is too complex to be applied to resource-constrained cameras. In this paper, based on 3-D sensing model and spatial geometric transformation, a 3-D application-oriented VC (3-D-AOVC) model is designed to quantitatively describe the correlation characteristics according to the specific application requirement. Furthermore, a 3-D VC coefficient (3-D-VCC) algorithm, which is aimed at the measurement of data redundancy is provided to elaborate the process of 3-D-AOVC model. Finally, utilizing the data redundancy measured by provided 3-D-VCC algorithm, a VC-based distributed energy efficient (VCDEE) scheme is devised. Experimental results show that the 3-D-AOVC model can accurately model the VC characteristics and the VCC algorithm has lower computational complexity and energy consumption than existing algorithm. Further simulation results demonstrate that the VCDEE scheme outperforms the state of the art in terms of energy conservation and balance.

关键词： 3-D visual correlation model application-oriented wireless visual sensor network energy efficient scheme

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A Real-time Object Detecting System using Compressive Sensing

A Real-time Object Detecting System using Compressive Sensin...

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IEEE International Conference on Signal Processing and Communication (ICSPC)

作者： Agrawal, Urvi Anil Jani, Preetida Vinayakray Sardar Patel Inst Technol Elect & Telecom Dept Bombay 400058 Maharashtra India

ISBN: (纸本)9781509067305

Nowadays, wireless visual sensor network (WVSN) is gaining significant importance and has several distinctive applications. WVSNs provides better results when it come to object detection since it consists of several tiny camera sensors which can capture the object's image and helps in identifying the object more precisely. There are some limitations of WVSN like battery constraints, limited storage memory so to overcome these limitations the proposed method is using block based compressive sensing technique (BCS) which applies compression only to the required blocks of image rather than applying it on whole image frame. The proposed method also incorporates a change detecting algorithm which will work only if the Mean square error (MSE) comparator crosses its predefined threshold value. The main aim of the proposed method is to achieve faster reconstruction of image with acceptable image quality so, to attain the required performance contourlet transform and projection driven compressive sensing recovery technique has been used. Also to increase the speed of reconstruction wiener filter is incorporated into iterative projected landweber compressive sensing recovery technique. The results have shown that the proposed block based compressive sensing with smooth projected landweber performs better than other methods as compared to quality of the reconstructed image.

关键词： Compressive sensing Contourlet transform Smooth projected landweber wireless visual sensor network

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Performance analysis of Real time Object Tracking System based on Compressive Sensing 4

Performance analysis of Real time Object Tracking System bas...

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4th IEEE International Conference on Signal Processing, Computing and Control (ISPCC)

作者： Agrawal, Urvi And Jani, Preetida Vinayakray Sardar Patel Inst Technol Elect & Telecom Dept Mumbai 400058 Maharashtra India

ISBN: (纸本)9781509058389

The main focus of Video Surveillance missions is to amass and verify data regarding appearance of object and position of target object. Such missions typically involve a high degree of covertness. Hence, for such sensitive applications there is desideratum for designing an unmanned surveillance system by using wireless visual sensor network. Because of bandwidth and energy utilisation bound of sensor nodes such systems necessitate less bandwidth and energy aware designs to ensure longevity of system. Therefore this paper proposes a compressive sensing based real time object tracking surveillance system that reduces bandwidth utilization by minimizing the amount of data required for processing. The system aims at minimizing the time required for image reconstruction, enhancing the quality of reconstructed image and reliable tracking of the moving object by reducing computational complexities in real time scenario. The paper attempts to reduce computational complexities and improve the quality of reconstructed image using Smooth Projected Landweber reconstruction technique. It also focuses on reducing the noise accumulated due to randomness of channel by operating under various modulations. Further, Kalman filter is used to track the object's path. To test the reliability of the proposed method, the performance of the system is evaluated under noisy channel using different modulation schemes.

关键词： Compressive sensing Channel modelling Kalman filter Smooth Projected landweber wireless visual sensor network

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Dynamic Resource Allocation for Compressive-Sensing-Based wireless visual sensor networks with Energy Harvesting

Dynamic Resource Allocation for Compressive-Sensing-Based Wi...

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International Conference on sensors, Measurement and Intelligent Materials (ICSMIM 2012)

作者： You, Lei Su, Xin Han, Yutong Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9783037856529

wireless visual sensor network (WVSN) is emerging with many potential applications. The lifetime of a WVSN is seriously dependent on the energy shored in the battery of its sensor nodes as well as the adopted compression and resource allocation scheme. In this paper, we use the energy harvesting to provide almost perpetual operation of the networks and compressed-sensing-based encoding to decrease the power consumption of acquiring visual information at the front-end sensors. We propose a dynamic algorithm to jointly allocate power for both compressive-sensing-based visual information acquisition and data transmission, as well as the available bandwidth under energy harvesting and stability constraints. A virtual energy queue is introduced to control the resource allocation and the measurement rate in each time slot. The algorithm can guarantee the stability of the visual data queues in all sensors and achieve near-optimal performance.

关键词： wireless visual sensor network energy harvesting compressive sensing power allocation energy queue

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Transmission Optimization of wireless visual sensor networks With Compressed Sensing Encoder

Transmission Optimization of Wireless Visual Sensor Networks...

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International Conference on Information Technology and Management Innovation (ICITMI2012)

作者： You, Lei Gao, Zhimin Han, Yutong Su, Xin Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9783037855744

The design and optimization of wireless visual sensor network (WVSN) is challenging due to error-prone wireless link, limited resource and low computational capacity. Traditional video coding methods and layered transmission protocols are not efficient for visual information collection in WVSNs. In this paper, we adopted the compressed sensing (CS) paradigm to sense and encode the visual information, and proposed a cross-layer transmission algorithm to achieve optimal trade-off between total distortion and power consumption by simultaneously controlling the CS measurement rate and allocating the power and bandwidth for each wireless link. The algorithm was obtained by using convex dual theory and sub-gradient iterative method. The optimality condition of the proposed algorithm was also given. The algorithm can be implemented in a practical WVSN in a distributed way with only limited local information exchanges.

关键词： wireless visual sensor network Compressed sensing dual decomposition distortion sub-gradient algorithm

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Binary Video Codec for Data Reduction in wireless visual sensor networks

Binary Video Codec for Data Reduction in Wireless Visual Sen...

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Conference on Real-Time Image and Video Processing

作者： Khursheed, Khursheed Ahmad, Naeem Imran, Muhammad O'Nils, Mattias Mid Sweden Univ Sundsvall Dept Informat Technol & Media Div Elect Design Stockholm Sweden

ISBN: (纸本)9780819494290

wireless visual sensor networks (WVSN) is formed by deploying many visual sensor Nodes (VSNs) in the field. Typical applications of WVSN include environmental monitoring, health care, industrial process monitoring, stadium/airports monitoring for security reasons and many more. The energy budget in the outdoor applications of WVSN is limited to the batteries and the frequent replacement of batteries is usually not desirable. So the processing as well as the communication energy consumption of the VSN needs to be optimized in such a way that the network remains functional for longer duration. The images captured by VSN contain huge amount of data and require efficient computational resources for processing the images and wide communication bandwidth for the transmission of the results. Image processing algorithms must be designed and developed in such a way that they are computationally less complex and must provide high compression rate. For some applications of WVSN, the captured images can be segmented into bi-level images and hence bi-level image coding methods will efficiently reduce the information amount in these segmented images. But the compression rate of the bi-level image coding methods is limited by the underlined compression algorithm. Hence there is a need for designing other intelligent and efficient algorithms which are computationally less complex and provide better compression rate than that of bi-level image coding methods. Change coding is one such algorithm which is computationally less complex (require only exclusive OR operations) and provide better compression efficiency compared to image coding but it is effective for applications having slight changes between adjacent frames of the video. The detection and coding of the Region of Interest (ROIs) in the change frame efficiently reduce the information amount in the change frame. But, if the number of objects in the change frames is higher than a certain level then the compression efficiency o

关键词： Video Coding Change Coding ROI Coding Image Coding wireless visual sensor network Energy Consumption

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Selection of bi-level image compression method for reduction of communication energy in wireless visual sensor networks

Selection of bi-level image compression method for reduction...

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Conference on Real-Time Image and Video Processing

作者： Khursheed, Khursheed Imran, Muhammad Ahmad, Naeem O'Nils, Mattias Mid Sweden Univ Sundsvall Div Elect Design Dept Informat Technol & Media Sundsvall Sweden

ISBN: (纸本)9780819491299

wireless visual sensor network (WVSN) is an emerging field which combines image sensor, on board computation unit, communication component and energy source. Compared to the traditional wireless sensor network, which operates on one dimensional data, such as temperature, pressure values etc., WVSN operates on two dimensional data (images) which requires higher processing power and communication bandwidth. Normally, WVSNs are deployed in areas where installation of wired solutions is not feasible. The energy budget in these networks is limited to the batteries, because of the wireless nature of the application. Due to the limited availability of energy, the processing at visual sensor Nodes (VSN) and communication from VSN to server should consume as low energy as possible. Transmission of raw images wirelessly consumes a lot of energy and requires higher communication bandwidth. Data compression methods reduce data efficiently and hence will be effective in reducing communication cost in WVSN. In this paper, we have compared the compression efficiency and complexity of six well known bi-level image compression methods. The focus is to determine the compression algorithms which can efficiently compress bi-level images and their computational complexity is suitable for computational platform used in WVSNs. These results can be used as a road map for selection of compression methods for different sets of constraints in WVSN.

关键词： wireless visual sensor network Communication Energy Consumption Computational Complexity visual sensor Nodes Image Compression

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Distributed Algorithms for network Lifetime Maximization in wireless visual sensor networks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2009年第5期19卷 704-718页

作者： He, Yifeng Lee, Ivan Guan, Ling Ryerson Univ Dept Elect & Comp Engn Toronto ON M5B 2K3 Canada Univ S Australia Sch Comp & Informat Sci Adelaide SA 5001 Australia

network lifetime maximization is a critical issue in wireless sensor networks since each sensor has a limited energy supply. In contrast with conventional sensor networks, video sensor nodes compress the video before transmission. The encoding process demands a high power consumption, and thus raises a great challenge to the maintenance of a long network lifetime. In this paper, we examine a strategy for maximizing the network lifetime in wireless visual sensor networks by jointly optimizing the source rates, the encoding powers, and the routing scheme. Fully distributed algorithms are developed using the Lagrangian duality to solve the lifetime maximization problem. We also examine the relationship between the collected video quality and the maximal network lifetime. Through extensive numerical simulations, we demonstrate that the proposed algorithm can achieve a much longer network lifetime compared to the scheme optimized for the conventional wireless sensor networks.

关键词： Convex optimization distributed algorithms network lifetime maximization power consumption wireless visual sensor network

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Joint Coding/Routing Optimization for Correlated Sources in wireless visual sensor networks

Joint Coding/Routing Optimization for Correlated Sources in ...

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IEEE Global Telecommunications Conference (GLOBECOM 09)

作者： Li, Chenglin Zou, Junni Xiong, Hongkai Zhang, Yongsheng Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China Shanghai Univ Dept Communicat Engn Shanghai 200079 Peoples R China

ISBN: (纸本)9781424441471

This paper studies a joint coding/routing optimization between network lifetime and rate-distortion, by applying information theory to wireless visual sensor networks for correlated sources. Arbitrary coding (distributed source coding and network coding) from both combinatorial optimization and information theory could make significant progress towards the performance limit of information networks and tractable. Also, multipath routing can spread energy utilization across nodes within the entire network to keep a potentially longer lifetime, and solve the wireless contention issues by the splitting traffic. The objective function not only keeps a total energy consumption of encoding power, transmission power, and reception power minimized, but ensures the information received by sink nodes to approximately reconstruct the visual field. Based on the localized Slepian-Wolf coding and network coding-based multipath routing, the balance problem between distortion (capacity) and lifetime (costs) is modeled as an optimization formulation with a distributed solution. Through a primal decomposition, a two-level optimization is relaxed with Lagrangian dualization and solved with the gradient algorithm. The low-level optimization problem is decomposed into a secondary master dual problem (encoding, energy, and congestion prices update) with four cross-layer subproblems: a rate control problem, a channel contention problem, a distortion control problem, and an energy conservation problem. Numerical results validate the convergence and performance of the proposed algorithm.

关键词： wireless visual sensor network distributed source coding network coding network lifetime rate-distortion

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