1. Object and Event Recognition in Wireless Multimedia Sensor Networks Clint Mueller CS441

2. Wireless Multimedia Sensor Networks (WMSN) Network of wirelessly interconnected sensor nodes equipped with multimedia devices (cameras and microphones) capable to retrieve video and audio streams, still images, as well as scalar sensor data.

3. Uses Military Law-Enforcement reports Traffic Control Advanced health care delivery Industrial Process Control Automated assistance to elderly telemedicine Autonomous processing vehicles (cars, robots, etc.)

4. Challenges High bandwidth Real time delivery Jitter and frame loss rate Object Recognition Techniques ▫Reduce information sent to sink node Nodes besides scalar nodes ▫Multimedia sensors ▫Processing hubs ▫Storage hubs

5. Network Architecture Divided into three reference models ▫Single-tier flat architecture ▫Single-tier clustered ▫Multi-tier architecture

6. Single-tier flat architecture Homogeneous sensor nodes All have same capabilities and functionalities Multimedia processing is distributed among all the nodes, and prolongs network life time

7. Single-tier clustered architecture Heterogeneous sensors Each cluster relay data to cluster head Cluster head performs the data processing Cluster head is connected to sink node or gateway

8. Multi-tier architecture Heterogeneous sensors First tier deployed with scalar sensors perform motion detection Second tier perform object detection or object recognition Third tier perform object tracking, connected to sink node or gateway Each tier may have central hub to perform data processing and communicate with higher tier

9. Physical Layer Ultra-Wide band (UWB) ▫Data rate up to 250 Mbps and range of 10 meters ▫Immunity to multipath propagation and precise positioning ▫Enable low power consumption ▫High data-rate or short range communication

10. MAC Layer Multi-channel MAC protocols which can effectively utilize the available channel capacity QoS based protocols COM-MAC ▫On-demand multi-channel contention-free ▫Better support for high data rates

11. MAC Protocals Grey rows indicate that the MAC protocol is designed for WSNs but not specifically for WMSNs.

12. Routing Layer Multipath routing because network needs to use all of its bandwidth Ant-based Service-aware (ASAR) ▫Addresses the routing scheme between the cluster head and sink node in which a cluster head transfers the different classes of data Two-Phase Greedy Forwarding (TFGF) ▫Geographic ▫Supports multipath transmission by repeatedly executing the algorithm to find more on-demand node-disjoint routing paths

13. Routing Protocols

14. Transport Layer Features of WMSN ▫Traffic: continues, event driven, query driven, hybrid ▫QoS: reliability, real-time delivery, fairness ▫High redundancy: reliability against packet loss Queue based Congestion Control Protocol with Priority Support (QCCP-PS) ▫Deal with congestion ▫Based on hop-by-hop approach

15. Transport Protocols

16. Application Layer Multimedia processing and source coding techniques Effective communication with other application programs Traffic management and admission control Applications: ▫Predictive Video Coding (PVC) ▫Multiple Descritption Coding (MDC)

17. Coverage Multimedia sensors do not have omni- directional coverage Snapshot ▫Automated calibration protocol ▫Calabrates the location, orientation, and range of camera sensor Knowing overlapping areas between cameras allows exploiting the redundancy and can be used to track moving objects in the environment

18. Object Recognition Edge Detection ▫Edges: boundary between two dissimilar regions in an image Address Event Representation (AER) ▫Extracts and outputs only a few features of interest from the scene ▫Only pixels which realize a difference in light intensity generate the events

19. Object Recognition Original, Edge Detection, and AER

20. Conclusion Do not stream the video but focus on tracking different events WSN protocols cannot be used in WMSN since WMSN has more constraints Object recognition is import in order to reduce the amount of data sent Coding techniques are used to reduce the redundancies in frames

21. References Image Recognition Traffic Patterns for Wireless Multimedia Sensor Networks – Ruekn Zilan, Jose M. Barcelo-Ordinas and Bulent Tavli; web http://www.academia.edu/4186077/Image_Recogn ition_Traffic_Patterns_for_Wireless_Multimedia_ Sensor_Networks http://www.academia.edu/4186077/Image_Recogn ition_Traffic_Patterns_for_Wireless_Multimedia_ Sensor_Networks Wireless Multimedia Sensor Networks: Current Trends and Future Directions – Islam Almalkawi, Manel Zapata, Jamal Al-Karaki and Julian Morillo- Pozo; web http://www.ncbi.nlm.nih.gov/pmc/articles/PMC32 31118/ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC32 31118/