Realization of Online Video Streaming in Wireless Multimedia Sensor Network with prolonging Battery life

Transcription

1 Volume No - 5, Issue No 2, March, 2017 Realization of Online Video Streaming in Wireless Multimedia Sensor Network with prolonging Battery life SHANMUGA PRIYAS 1 st Department of ECE Parisutham Institute of Technology and Science Thanjavur, India spriya3192@gmailcom ABIRAMIS 2 nd Software Engineer, Mind Space, Airoli Navi Mumbai abigemini@gmailcom Abstract: Various applications like wildlife monitoring, video surveillance, traffic monitoring, and license plate recognition are done using either image or video processing by a camera unit The capabilities of wireless sensor networks are restricted because of inadequate power demand In Wireless multimedia Sensor Networks (WMSN), each node has camera module and communication is done via Wi-Fi, Bluetooth or radio frequency module supported by battery power source In the proposed work, two working modules are being designed (i) Detection of human in unmannered area using WMSN (ii) An algorithm to detect battery power level In detection of human the Passive Infrared sensor (PIR) sensor is used for human movement discovery and a controller unit has a camera module along with driver circuit per MxN grid The object detection done by PIR sensor and tracking is done by rotatable camera The battery power model algorithm is used to detect and alarm the information about the nodes with low battery power to a monitoring node Thus, node failure due to battery drain can be prevented These two modules help the user to have knowledge about the entire multimedia network and can make any alternate arrangement if any node demands for power The hardware setup is implemented and the results are shown using PC Keywords: Wireless multimedia sensor network (WMSN), Passive infrared sensor (PIR), Wireless camera, Battery power model I INTRODUCTION Wireless multimedia sensor networks (WMSN) consists of devices organized wirelessly which allows capturing video and acoustic streams, still images and scalar sensor data Currently, the availability of low-cost hardware such as Complementary Metal-Oxide Semiconductor (CMOS) cameras as well as microphones captures multimedia information in real time and transmits over the established network to base station Normally object detection done with image capturing sensors is also efficient but when comparing the knowledge gained by an image, video have better learning capability With the aid of highly developed image and video processing techniques, identification of person/target/terrorist within the region of interest can be detected IEEE standard consisting of physical and MAC layers are generally used in WSN [1] The current developments and contribution of many researchers in the field of WSN, IS demanding more assets similar to reminiscence, power, band width plus complex computational capabilities The IEEE transceiver has advanced and adjustable data rates of 1, 2, 11 and 54 Mbps, that afford higher bandwidth of 20 MHz as contiguous to the IEEE standards data rate of 250 kbps and 2 MHz bandwidth Comparing the Bluetooth and Zigbee for supporting multimedia application, Zigbee is preferred than Bluetooth due its limitations like low density of nodes, high cost and power consumption Zigbee uses multipath routing techniques which saves power The major objective is to establish a cost effective sensor network, which may result in faulty nodes due to random deployment in hostile environment [2] The node failure includes battery drain, physical sensor failure, and circuit failure in the node, link failure in communication between the host node and the end node, other hardware and software failures Where, RES Publication 2012 Page 75 wwwijmeceorg II PROPOSED WORK A Detection of Human in unmannered area Considering an area of interest where the human motion must be detected, the sensors are pre- deployed physically The monitoring area is divided into predefined square sections and for each square grid the placement of sensors is done such that less correlation occurs within the coverage area of each node In a grid, the PIR sensor nodes are placed in the corners and wireless camera node is positioned in the center of the grid The sensing range of PIR sensor is about minimum 3m to maximum 5m The sensitivity range of sensor can be adjusted according to the requirement The coverage of camera is about minimum 8m and maximum 12m The FOV of the camera must satisfy the estimated coverage range The deployment design should consider the coverage range requirements for various field monitoring purposes For the sensing field M N, [3] the estimated coverage must satisfy the condition Б <= M N The 2D model of coverage area can be given as, Б α (X, Y, ᴨ, θ, R) (1)

2 Volume No - 5, Issue No 2, March, 2017 Б Estimated coverage (X, Y) Vicinity of the camera lens ᴨ - Direction of the camera θ Maximum discovery angle R Maximum exposure radius As stated in (1), the coverage depends on all the parameters which has an adverse effect in the video captured from the event detected field The alignment of camera must be taken care in such a way that its field of view covers the estimated range The received video is viewed on the base station The base station as shown in the Figure 2, the video is received using zigbee and the PC runs AMcap software where the received video can be viewed, saved, retrieved etc, for further analysis After detecting the abnormal activity, suitable guard alert process can be actuated Figure 2: Block Diagram of Monitoring System B Battery power model Algorithm Figure 1: Block Diagram of PIR and Wireless camera Implementation module Figure 1 illustrates the block diagram of the planned scheme, and it is cited in the monitoring field Each monitoring node has PIR sensor and a controller unit which transmits the Motion detected message to the camera controller unit when human motion is detected in its area So a threshold is maintained in such a way that if the incoming thermal value exceeds the cut off value, Motion detected message will be transmitted to the central camera unit [5] The controller after receiving the message analyzes the activity detected area and the camera is rotated to that corresponding activity recognized position The camera movement is achieved using DC motor and driver circuit The DC motor speed can be adjusted by the user with respect to the application; both high and medium speed can be used The video streaming is done once the estimated position is reached If the activity is detected in one region, the camera will be focused towards that region Another case, if the activity occurrence appears more than one region, the camera rotates continuously and would cover all areas It is capable of capturing 30 frames per second As shown in Fig 2, the hardware module is set up An AVR 8 bit microcontroller is used which is of low power consumption, high performance with 4kbytes of programmable flash memory and connected with the following components, a zigbee module for communication, a battery level indicator for displaying the percentage of battery available and a temperature sensor The battery status monitor is used to recognize whether the node is in full battery condition or not It has four nodes with each performing the work of sensing and sending the value to the end system via the zigbee module The problem arises when one of the node s battery power (say Node 1) reaches below the threshold value and the Battery power model algorithm is made to run in the corresponding AT89C51 controller to transfer the data to the next lying highest power battery node (say Node 3)The Node 3 then transfers the value of its own sensor readings along with the value of the Node 1 which can extend the lifetime of the Node1 and makes it to sustain a longer time As the three Nodes are placed in equidistant to each other the distance between the two sensor nodes is less [4], compared to the distance between the sensor node and the end system Where Pt Power used for transmission Pr (d) Power used for reception d Distance between transmitting and receiving units C f Constant RES Publication 2012 Page 76 wwwijmeceorg

3 Volume No - 5, Issue No 2, March, 2017 device decides the role of the device in the organization, and called as type of device 3 WIRELESS A/V CAMERA: RM0100 is a Wireless Audio/Video camera with more sensitivity range of about high +18dB and the acknowledged signal portrait sound 09G/12G with high quality production It works on 24 GHz wireless camera in the ISM band It has 380 TV analog lines which belong to Hi8 video format Low resolution camera is used in the experiment analysis Hence the video quality will be with medium quality B Module 2: Fig 3: Block diagram of battery power model As the distance get increases, the transmission power get increases which results in high energy consumption In a real time monitoring environment, if the Node 1 (which lowers below the threshold value) sends its value to the end system directly, it consumes higher power consumption and leads to extinction of that node To avoid the node failure and extend its life time, the Battery Power Model algorithm is proposed III EXPERIMENTAL ANALYSIS A Module 1: The experimental setup has been made using two nodes with one camera node used for field monitoring and the monitoring station has a Controller unit with Zigbee module to receive the processed output video ATMEGA 16 controller is used for operations such as PIR sensing for human activity detection and video streaming at the receiver area 1 AVR controller: AVR microcontroller with high performance and 16 KB of In-built programmable flash is used in field monitoring nodes and also in monitoring station It is a low power CMOS 8-bit microcontroller which works on renovated RISC design and also optimizes power consumption against processing speed Fbp is Full battery power Kbp is the Battery level of the node at the current time Tbp is the threshold battery power set The first step describes that every node checks its own battery power Kbp with the full battery power Fbp and a Threshold battery power Tbp is set for each node The current battery power Kbp is made to compare with the Threshold battery power in a loop basis and if the current battery power is less than the threshold battery level then, it sends request to the other neighboring nodes The node with the highest battery power is chosen and the handoff methodology is done 2 CC2530 ZigBee module: Every device should execute precise networking functions and also must alignment of certain parameters to explicit values must be predefined The set of functions to be performed by a RES Publication 2012 Page 77 wwwijmeceorg

4 Volume No - 5, Issue No 2, March, 2017 C Integration flow chart: For demo purpose, the area t be monitored is about 10x10 grid and hence two motion detecting nodes were used namely Camera 1 for first node covering a particular area say 5m and Camera 2 for another node covering the remaining area say about 5m Again the PIR sensitivity range can be varied according to the user requirement Figure 5: Still image from the received video The received video stream is viewed in laptop running with AMcap software, as shown in Figure 5, which executes the SMI grabber and USB 20 for receiving the video via USB port This simplifies the video reception process AMcap is software that helps to capture still image or video using the webcam available in the Laptop B Module 2 Demo: A Module 1 Demo: IV RESULTS The human detected message is delivered in monitoring station and also indicates in which node the activity occurs As shown in Figure 4, the Human detected message is displayed in LCD for demo purpose and the activity detected node is specified as camera 1 Each node consist of three AVR controllers which collect information about the temperature, humidity and gas values from the corresponding sensors connected with the controller The corresponding sensor values are transmitted to the monitoring node via the zigbee module The Node1 consists of Tiny AVR 8 bit controller, a LCD for displaying the battery power, and a 12V Battery for power supply to the circuit with the temperature sensor connected to it Figure 4: Monitoring Station Unit Figure 6: AVR with Temperature sensor RES Publication 2012 Page 78 wwwijmeceorg

5 Volume No - 5, Issue No 2, March, 2017 REFERENCES [1 ]Gareth Mitchell, "The Raspberry Pi single-board computer will revolutionize computer science teaching", [For & against], vol 7, no 3, pp 26, 2012 [2] Charles Severence, "Eben Upton: Raspberry Pi", vol 46, no 10, pp 14-16, 2013 [3] Matt Richardson, Shawn Wallace, Getting Started with Raspberry Pi, United States of America: O'Reilly Media, 2013 [4] J Y Hao, H Shen, C Li, Z Xiong, and E Hussain, Vehicle behaviour understanding based on movement string, in Proc 12th Int IEEE ConfIntell Transp Syst, 2009, pp Figure 7: AVR with Humidity Sensor [5] J Yao and J M Odobez, Multi-layer background subtraction based on color and texture, in Proc IEEE CVPR, 2007, pp1 8 AUTHOR S BIOGRAPHIES SShanmuga Priya completed her bachelor s degree in Electronics and Communication Engineering at Parisutham Institute of technology and Science College affiliated Anna university in the year 2013 and her Master Degree in Embedded Systems at SASTRA University in the year 2015 She is working as Assistant Professor in the department of Electronics and Communication Engineering of Parisutham Institute of Technology and Science Her area of interest includes Embedded System, Wireless Networks and RTOS Figure 8: AVR with Gas sensor Similarly the Node2 and Node3 consist of same set up with humidity and gas sensor connected As per the algorithm, when the Node1 gets below the threshold value it detects its own battery level and sends its parameters ie, sensor readings to the neighboring node which has the highest battery power among the other nodes in the mesh network V CONCLUSION In this paper, the initial deployment of a network with sensors and wireless camera for human monitoring in unmanned area is deployed The proposed new low cost network establishment with PIR and camera satisfies the computing and energy saving criteria s The FoV of the camera is also considered during the design phase Since the activation of the camera is event driven, the energy is saved as much as possible The number of camera nodes deployed in the field is reduced and normal nodes with PIR sensors are deployed more And also transmission of messages between the nodes is eliminated and the complete transaction is done only between sensor node and camera node within its coverage range Battery Power Algorithm is implemented in the real time which extends the life time of the node SAbirami completed her bachelor s degree in Electronics and Communication Engineering at Anjalai Ammal Mahalingam Engineering College affiliated Anna university in the year 2013 and her Master Degree in Embedded Systems at SASTRA University in the year 2014 She is working as Software Engineer, Mind Space, Airoli, Navi Mumbai Her area of interest includes Microprocessors and Embedded systems RES Publication 2012 Page 79 wwwijmeceorg