This document discusses detecting proximity events in sensor networks. It introduces the concept of proximity queries, which allows sensor nodes to report interesting events observed within a certain distance of each other. It describes how sensor nodes scattered in a sensor field can detect proximity events using local routing indices and transmit data along predefined or unknown paths. It addresses problems that can occur, such as wasted messages when no matching events are nearby, and presents solutions like rumor-based approaches and incrementally updating local routing indices.

1. DETECTING PROXIMITY
EVENTS IN SENSOR
NETWORKS
By
Balasuresh A –PR12CS1011

2. OBJECTIVE
 To show a simulation of Vehicle Tracking in defined path as
well as unknown path in the terrain.
 Our Technique is to handle moving events
 We introduce the concept of Proximity Queries, which allows us
to report interesting events, observed by the nodes in the network
that lie within a certain distance from each other.

3. INTRODUCTION
 Sensor networks are often used to perform monitoring tasks
 concept of proximity queries - event is triggered when a user-
programmable predicate is satisfied on a sensor node
 everything based on the distributed routing index, and it is
maintained by the nodes in the network

4. WHAT IS PROXIMITY ?
 The quality or state of being next in time, place etc.;
 Immediate nearness, either in place, alliance.
Proximity Sensors
• A Proximity Sensor is a sensor able to detect the presence of
nearby objects without any physical contact.
• Different Proximity Sensors are there:
 Plastic detection – Photoelectric Proximity Sensor.
 Metal detection – Inductive Proximity Sensor.

5. COMPONENTS OF A
SENSOR NODE

6. SENSORS NODES
SCATTERED IN THE
SENSOR FIELD

8. TOPOLOGY

10. TRANSMITTING DATA

11. UNKNOWN PATH

12. WHAT ARE THE THINGS
INCLUDED
 to correlate observations on different sensors - straightforward
implementations based on localized flooding - external processing
algorithms
 local indexing structures – maintaining routing index
 Bandwidth efficient algorithms - detecting proximity - designed
to handle moving event (i.e.) move along predefined or unknown
paths in the terrain.

13. Random-walk techniques
 Target at k different nodes – this technique will direct until
reaches its one of the k different destination.
spatial-temporal suppression techniques:
 reducing the cost of monitoring queries in sensor networks.
local routing table:
 In order to compute the next hop to route a message is
fundamental in the Border Gateway Protocol (BGP)

14. PROBLEMS OCCUR AND
THEIR SOLUTION
(i) Sometimes we may get, like a problem of a situation where a
lot of messages are wasted when no matching events are in the
neighborhood.
Solution:
Ssrc observes an event X, it initiates a search for matching events
- at the same time the nodes that have observed these matching
event-

15. (ii)Locating of events in the Corresponding Sensor Network
Solution:
rumor-based approach - utilizes agents that upon the detection
of an event traverse the network propagating information about the
event.
routing indices are maintained locally and are never
transmitted in the network - these indices are updated ‘‘incrementally’’
upon the announcement of an event.

16. (iii)Identify the neighbor node, to transmit the messages and
communication
Solution:
- GPSR (Greedy Perimeter Stateless Routing)
- allows point-to-point communication
- distant wireless nodes using the positions of the nodes
- packet’s destination to make packet forwarding
 Data-centric techniques

18. ROUTING INDICES
 2 major operations :
(i) How to update the routing index when the node receives
information on new events
(ii) Given the routing index, how to determine the next hop list NH
of the node

19. ISSUES
1) Track of packets, in between two nodes
2) Sometimes, if the two nodes received the same event, it is
difficult to find the target node by both of them.
3) Synchronize between two nodes indices.
4) Memory requirement for Indices.
5) Packets loss

20. CONCLUSION
 Our algorithms do not assume any specific sensor topology and
can also be applied to cases of clustered organizations.
 Accident detection – Service details

21. THANK YOU