1. SNoD Sensor Networks on Defense Team Members: Kaustubh Supekar Gaurav Sharma Deepti Agarwal Aditya Barve Brijraj Vaghani Seema Joshi Debashis Haldar Gautam Kaushal

2. Smart Dust eh!!! The particles of dust that could be watching you .
Smart Dust is the brainchild of Associate Professor Kris Pister and Professor Randy H. Katz, who are currently working at the University of California, Berkeley

3. Techie definition
Smart Dust Sensor (also known as a sensor mote) is a tiny wireless micro-electromechanical sensor (MEMS) packed into a cubic millimeter speck that can detect anything from light to vibrations.

4. Mote Constraints Power, size and cost These get translated to
Slow clock cycles of the micro controller.
Less memory.
Smaller number of hardware controllers.

5. MOTE Specifications Two Board Sandwich Size CPU Memory Radio
CPU/Radio board
Sensor Board: temperature, light
Size
Mote: 11 in
Pocket PC: 5.23.1 in
CPU
Mote: 4 MHz, 8 bit
Pocket PC: 133 MHz, 32 bit
Memory
Mote: 512 B RAM; 8K ROM
Pocket PC: 32 MB RAM; 16 MB ROM
Radio
900 Hz, 19.2 kbps
Bluetooth: kbps
Lifetime (Power)
Mote: 3-65 days
Pocket PC: 8 hrs

6. Sensor Network
A collection of sensor motes that perform autonomous sensing to form the basis of a massively integrated sensor network which sends some useful information to a base station.
Some examples:
Environmental sensor networks to detect and monitor environmental changes.
Wireless surveillance sensor networks for providing security in a shopping mall, parking garage, etc.
Military sensor networks to detect enemy movements, the presence of hazardous material.

7. Sensor Vs Ad-Hoc Networks
The number of sensor nodes in a sensor network are much more than in an ad-hoc network.
Sensors act with other sensors in a restricted vicinity.
The topology of a sensor network changes more frequently.
Sensor nodes mainly use a broadcast paradigm, whereas most ad-hoc networks are based on a point-to-point communication
Sensors are more constrained in memory and energy compared to ad-hoc networks.
Sensors interact with physical environment, they experience Task Dynamics.

8. Our Aim
Deploy a large number of sensor motes to form a network to monitor movements of human beings in a terrain.
The sensor motes communicate and co-ordinate efficiently to establish an approximate count of the number of human beings in that terrain.

9. Requirements
Large number of sensors which remain stationary after random deployment.
Low energy usage (Computationally light execution and minimal amount of energy transmission)
Self-organizing network
Collaborative signal processing (Data aggregation)
Security

10. Human detection PIR sensors
Passive Infrared Sensors detect infra-red heat energy emitted by humans. Triggering occurs when they detect a change in infrared levels, as and when a warm object moves in or out of range of a sensor. They are quite resistant to false triggering.

11. Salient Features
A localized clustering algorithm that contributes to scalability, robustness and efficient utilization of resources.
A routing algorithm that adapts itself to the dynamics of the network and changes in the clusters.
A data aggregation algorithm to fuse data from multiple sensors within a cluster.
Security features that ensure only authorized users are granted access to the network and only those messages that weren’t altered in transit are accepted.

12. Clustering
Allows to efficiently co-ordinate local information and thus contribute to scalability, robustness and efficient utilization of resources.
Each cluster is formed during bootstrap and all the members of a cluster elect a cluster head, which performs data aggregation and routing for the cluster.

13. After PROMOTION TIMER expires, if a sensor hasn’t received any other sensor’s advertisement declaring itself as the Cluster Head, then the sensor promotes itself as the cluster head.
All sensors start advertising presence within a predefined broadcast range and start WAIT TIMER.
All non-cluster heads choose their cluster head and form clusters.
Cluster heads
All cluster heads send advertisements to the sensors from which they received presence advertisements.
By the end of the WAIT TIME all the sensors would have received advertisements from the sensors within its broadcast range. All sensors then start their PROMOTION TIMER, which is inversely proportional to the energy level of the sensor and number of advertisements it received.

14. Routing
Base station
w01
w04
Level 0
w02
w03
w11
w12
Level 1
(W01*w11 + w02*w12) / 2
Only the clusters not within Level 0 listen to those messages and again calculate their own weight based on the received messages’ signal strength. These clusters are at Level 1.
All the cluster heads receiving this message set themselves as Level 0 members and assign weight to themselves based on the received RF signal strength from the base station and send back acknowledgements.
Level 0 cluster heads now propagate another message within a limited range for other cluster heads.
Base station sends a message within a limited range so that only nearest cluster heads receive it.

15. Communication amongst Sensors
Since all sensors within a single cluster operate at the same frequency, provisions have to be made such that the signals do not interfere with each other .We overcome this problem by using CSMA/CA.
Similarly even the cluster heads when sending information to a lower level or to the base station use the same technology

16. Future Work Implementation of Security Features
Data Aggregation of information from various sensors.
Fine tuning of routing and clustering algorithms.
Parallel processing of Clustering and Routing algorithms, the current version works sequentially
Simulation of the algorithms to test their validity.

17. Applications Location and quantity detection in a Warehouse.
Disaster detection and recovery which today by comparison is very human intensive.

18. Q&A