Solar-powered, wireless smart camera network: An IoT solution for outdoor video monitoring

Abstract In this paper, we present SlugCam, a solar-powered, wireless smart camera network that can be used in a variety of outdoor applications including video surveillance of public spaces, habitat and environmental monitoring, wildfire prevention and detection, to name a few. SlugCam was designed such that it can be deployed and left unattended for extended periods without requiring regular maintenance, e.g., frequent battery replacement. The system is built with off-the-shelf components which not only keeps it modular and low cost, but also facilitates its prototyping, rapid duplication, and evolution. SlugCam’s on-board processing capability allows computer vision software to run locally and autonomously. Energy efficiency in SlugCam is accomplished both in: (1) hardware by micro-managing low-power components; as well as in (2) software by having the system’s operation duty cycles automatically adapt to the current state of the battery in order to balance the trade-off between application-level requirements and power awareness. For example, SlugCam’s smart camera node changes its monitoring behavior based on how much battery charge remains. Additionally, using its computer vision software, the system only records and transmits information upon event detection which contributes both to the system’s energy efficiency as well as its low network bandwidth requirements. SlugCam’s networking functionality enables camera nodes to transfer video files, as well as collaborate on tasks such as visual processing, event detection, and object tracking. It allows node-to-node, as well as scoped- or full broadcast communication. For point-to-point communication, SlugCam uses on-demand power-aware multi-path routing to transfer video files efficiently. Another important contribution of SlugCam is to provide an open-source wireless camera network that can adapt to address the requirements of future outdoor video monitoring applications. SlugCam also includes a Web-based server where video data is stored as well as a Web-based user interface that allows end users to interact with the system, tag, query and retrieve video files, and manage SlugCam nodes remotely. In addition to a detailed description of SlugCam, this paper presents an extensive power characterization of the system’s operation and showcases its deployment in a lab testbed and a real world scenario.

[1]  JAMAL N. AL-KARAKI,et al.  Routing techniques in wireless sensor networks: a survey , 2004, IEEE Wireless Communications.

[2]  Kah Phooi Seng,et al.  Ant Based Routing Protocol for Visual Sensors , 2011 .

[3]  Martin Reisslein,et al.  Towards Efficient Wireless Video Sensor Networks: A Survey of Existing Node Architectures and Proposal for A Flexi-WVSNP Design , 2011, IEEE Communications Surveys & Tutorials.

[4]  Tieniu Tan,et al.  A survey on visual surveillance of object motion and behaviors , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[5]  Anthony Rowe,et al.  Real-Time Video Surveillance over IEEE 802.11 Mesh Networks , 2009, 2009 15th IEEE Real-Time and Embedded Technology and Applications Symposium.

[6]  Gorry Fairhurst,et al.  WiseEye: Next Generation Expandable and Programmable Camera Trap Platform for Wildlife Research , 2017, PloS one.

[7]  Ashley Tews,et al.  Real-Time Object Tracking and Classification Using a Static Came ra , 2009 .

[8]  Pamela Zave,et al.  Requirements for Routing in the Application Layer , 2007, COORDINATION.

[9]  Ahmed Patel,et al.  Comparative review study of reactive and proactive routing protocols in MANETs , 2010, 4th IEEE International Conference on Digital Ecosystems and Technologies.

[10]  Michele Magno,et al.  A Solar-powered Video Sensor Node for Energy Efficient Multimodal Surveillance , 2008, 2008 11th EUROMICRO Conference on Digital System Design Architectures, Methods and Tools.

[11]  Sungjin Lee,et al.  Optimization of Delay-Constrained Video Transmission for Ad Hoc Surveillance , 2014, IEEE Transactions on Vehicular Technology.

[12]  Richard M. Voyles,et al.  Wireless Video Sensor Networks over Bluetooth for a Team of Urban Search and Rescue Robots , 2006, ICWN.

[13]  Artemios G. Voyiatzis,et al.  A secure DTN-based smart camera surveillance system , 2011 .

[14]  S. Voliotis,et al.  Enabling QoS in Visual Sensor Networks , 2006, Proceedings ELMAR 2006.

[15]  Zhe Zhang,et al.  Analysis of the accuracy-latency-energy tradeoff for wireless embedded camera networks , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[16]  W. Richard Stevens,et al.  Unix network programming , 1990, CCRV.

[17]  Michele Magno,et al.  Multimodal Video Analysis on Self-Powered Resource-Limited Wireless Smart Camera , 2013, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[18]  Mani Srivastava,et al.  Energy efficient routing in wireless sensor networks , 2001, 2001 MILCOM Proceedings Communications for Network-Centric Operations: Creating the Information Force (Cat. No.01CH37277).

[19]  Allen Y. Yang,et al.  A low-bandwidth camera sensor platform with applications in smart camera networks , 2013, TOSN.

[20]  Yongguang Zhang,et al.  System Services for Ad-Hoc Routing: Architecture, Implementation and Experiences , 2003, MobiSys '03.

[21]  Katia Obraczka,et al.  Wireless Smart Camera Networks for the Surveillance of Public Spaces , 2014, Computer.

[22]  S. Kim,et al.  Trio: enabling sustainable and scalable outdoor wireless sensor network deployments , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[23]  Purushottam Kulkarni,et al.  Energy Harvesting Sensor Nodes: Survey and Implications , 2011, IEEE Communications Surveys & Tutorials.

[24]  Eugenio Culurciello,et al.  A Lightweight Camera Sensor Network Operating on Symbolic Information , 2006 .

[25]  S. Voliotis,et al.  Open issues in Wireless Visual Sensor Networking , 2007, 2007 14th International Workshop on Systems, Signals and Image Processing and 6th EURASIP Conference focused on Speech and Image Processing, Multimedia Communications and Services.

[26]  Xiaohua Jia,et al.  Rate-adaptive broadcast routing and scheduling for video streaming in wireless mesh networks , 2014, 2014 23rd International Conference on Computer Communication and Networks (ICCCN).

[27]  Alfio Lombardo,et al.  Multipath routing and rate-controlled video encoding in wireless video surveillance networks , 2008, Multimedia Systems.

[28]  Ling Guan,et al.  Optimal resource allocation for video communication over distributed systems , 2009, 2009 IEEE International Conference on Multimedia and Expo.

[29]  Shree K. Nayar,et al.  Towards Self-Powered Cameras , 2015, 2015 IEEE International Conference on Computational Photography (ICCP).

[30]  Michele Magno,et al.  Benefits of Wake-Up Radio in Energy-Efficient Multimodal Surveillance Wireless Sensor Network , 2014, IEEE Sensors Journal.

[31]  Richard Han,et al.  FireWxNet: a multi-tiered portable wireless system for monitoring weather conditions in wildland fire environments , 2006, MobiSys '06.