1 Emergency Navigation by Wireless Sensor Networks in 2D and 3D Indoor Environments Yu-Chee Tseng Deptment of Computer Science National Chiao Tung University

2 Outline Introduction System Overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion

3 Outline Introduction System Overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion

4 Introduction Wireless Sensor Network Each sensor has Limited Memory 、 Limited CPU 、 Wireless Transceiver 、 Sensing Unit Each sensor can Sense environments Communicate with others Do simple computations

5 Introduction Traditional Navigation Devices Advantage Cheap Easy deployment Disadvantage Fixed direction. Can not adapt to actual emergency situations.

6 Introduction Motivation According to the statistic report of the NFA of Taiwan( 內政 部消防署）, 228 people died in fire accidents in The main reason is that people can not find “right” escaping paths to exits. Our Goal to develop an emergency navigation system for indoor 2D and 3D environments

7 Outline Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion

8 System Overview Our system is composed of 3 parts Environment setting Regular reporting Emergency Navigation Two network graphs Communication graph and guidance graph Communication graph Guidance graph

9 Environment Setting Deploy sensors Construct reporting tree Setup initial navigation paths navigating reporting

10 Outline Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion

11 Deployment of Sensors Plan locations of sensors Define the roles of sensors Sink Exit sensors Normal sensors Decide navigation links navigation links (for human)

12 Construct a Reporting Tree Step 1. Discover symmetric links Each sensor periodically broadcasts HELLOs When receiving a HELLO, sensors reply ACKs After receiving an ACK, sensors record the sender ID in its link table HELLO ACK Link table

13 Construct a reporting tree (cont.) Step 2. Construct a spanning tree Sink floods a BEACON. For a sensor receives a BEACON, it checks if the sender is in its link table If yes, it sends a REG(ister) to sink and rebroadcasts BEACON. Else, drops it BEACON REG BEACON

14 communication links (for packets)

15 Outline Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion

16 Reporting Issues How often a report should be sent? Will each sensor report individually? Is there any inaccuracy? False alarm? How to save energy of sensors?

17 Outline Introduction System overview Environment setting Regular report Emergency navigation in 2D environment Simulation results Demonstration Conclusion

18 Design Principle When a sensor detects an emergency event, it forms a hazardous region The navigation algorithm will try to guide people as farther away from hazardous regions as possible

19 Problem Formulation Each sensor has an altitude. Sensors in hazardous regions will raise their altitudes. Each sensor guides people to the neighbor with the lowest altitude After forming hazardous regions, some sensors may become local minimum ones A partial link reversal operation is performed to solve this problem

20 Phases of Navigation Initialization phase Initial phase is started by Exit sensor After this phase, every sensor has a default guiding direction. Navigation phase This phase starts by the sensor which detects an emergency event.

21 Terminology D ： The radius of the hazardous region A emg ： A large constant which represents the maximum altitude A i ： The altitude of sensor i I i ： The altitude obtained in the initialization phase e j,i ： The hop count from emergency sensor j to sensor i

22 Initialization phase Every exit sensor sets its altitude to 0 and broadcasts an initialization packet. When receiving an initialization packet, a sensor adds its hop count by 1. Then, it compares the hop count with its current altitude ∞∞∞ ∞∞∞ ∞∞∞ 0

23 Initialization phase (cont.) If the hop count is smaller than its altitude, it resets its altitude and setups its initial guiding direction to that sender. Then, it rebroadcasts this packet. ∞∞ ∞∞∞ ∞∞∞

24 Navigation phase When a sensor x detects an emergency, it will set its altitude to the maximum altitude A emg (let it be 200). Then it broadcasts an emergency packet EMG(seq, x, x, A emg, 0) seq ： sequence number x ： emergency ID w ： sender ID A w ： altitude of sender h ： hop count to emg. location

25 Navigation phase (cont.) When a sensor node y receives a EMG packet originated from node x, it will do the following steps. Step1 : Decide that the emergency is a new one or not  If it’s a new emergency, record this event and set the hop count e x,y to h+1.  Else, compare the h and e x,y. If h is smaller than e x,y, set e x,y to h+1. Record the altitude (A w ) in the navigation link table

26 Navigation phase (cont.) Step 2: If e X,Y was changed in step1 and e X,Y ≦ D, y considers itself within hazardous region. Then it re-calculates its altitude as follows ：

27 Navigation phase (cont.) Step 3 : If y has a local minimum altitude and it’s not an exit, it must adjust its altitude as follows ： = altitudes of y’s neighbors STA = standard deviation  A bigger value means closer to the hazardous region. So we need to adjust the altitude faster. |N y | = number of neighbors of y.  A smaller | N y | means less escape ways. So we need to adjust the altitude faster. δis a small constant Static adjustment Our scheme Five iterations Three iterations

28 Navigation phase (cont.) Step 4: y has to broadcast an EMG(seq, x, y, A y, e x,y ) packet if any of the following conditions matches.  It’s a new emergency  y has changes its altitude or e x,y in the previous steps. Step 5: If y is in hazardous regions and it sees an exit sensor which is in N y and which is also in hazardous regions, then y chooses this exit sensor In all other cases, y directs users to a safer sensor first, and then gradually to a safe exit.

29 Example— Altitude after initial phase Exit 10x10 Grid Network

30 One emergency event – after step 1, 2 & 4 Local minimum

31 One emergency event– final result

32 Two emergency events– after step 1, 2 & 4 Local minimum

33 Two emergency events– final result

34 Outline Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion

35 Simulation results We compare our navigation algorithm with “ Distributed algorithm for guiding navigation across a sensor network” (MobiCom 03) This algorithm guides people to the nearest exits However, nearest exits may not be good choices

36 Simulation results Case1. Our algorithm will choose to pass hazardous region areas as farther away from emergency locations as possible. Case2. Our algorithm will not guide people passing through the hazardous region. Case3. Only the sensors near the exit in the hazardous region will guide people to that exit.

37 Outline Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion

38 Demonstration System Components MICAz sensors Environment monitoring Navigation Sink MIB510 serial Gateway Gateway between wireless sensor network and PC PC Control Host

39 Demonstration exit (normal time) first event (emergency time) second event (emergency time)

40 A Short Summary (2D) Novel indoor monitoring and navigation services based on wireless sensor network technolgoies emergency will raise sensors’ altitudes navigation similar to TORA protocol, but different in that emergencies will disturb altitudes altitude adjustment is designed for quicker convergence navigation in emergency applications requires safer paths, but not necessarily longer paths

41 Emergency Navigation in Indoor 3D Environments by Wireless Sensor Networks Yu-Chee Tseng Department of Computer Science National Chiao Tung University

42 Introduction Why 2D guiding algorithms can’t directly apply to 3D environments room 2F room 3F room 1F room 2F Rooftop room

43 System Architecture

44 Guidance initialization (0, 0) (0, 1) (0, 2)(0, 1) (0, 2) (1, 0) (0, 3) (1, 1) 1F 2F a b c d e f

45 Guidance initialization 3F room 2F 1F 4F (0,0)(0,1) (1,0) (0,0) (0,2)(0,0)(0,1) (0,1)(0,1) (0,2)(0,3)(0,2)(0,1) (0,2)(0,1)(0,2) (1,1) (1,0) (1,2)(1,2)(1,3) (1,1)(1,1) (1,2)(1,3)(1,2)(1,1) (1,2)(1,3)(1,2) (2,1) (2,0) (2,2)(2,2)(2,1) (2,1)(2,1) (2,2)(2,3)(2,2)(2,1) (2,2)(2,3)(2,2) (2,0) (3,1) (3,0) (3,2)(3,1)(3,2) (3,1)(3,1) (3,2)(3,2)(3,1)(3,1) (3,1)(3,0)(3,1) (3,0)

46 Principles of 3D guidance A sensor is located in a hazardous region if it is D hop away from the emergency point or it’s a stair sensor and its downstair sensor is in a hazardous region When guiding Avoid to guide people through hazardous regions Try to guide people to the exits on the ground floor Guide people to rooftop if there is no proper ways to downstairs

47 Simulation results

48 Prototyping We have implemented our system using MICAz motes and MTS310 sensors on TinyOS. Protocol stack

49 JAVA GUI

50 Guidance UI

51 Demonstration Environment A virtual 2-store building

52 Demonstration Vedio

53 More Results

54 Conclusions Extending 2D navigation to 3D navigation on each floor, the navigation is similar to 2D stair and gateway sensors are paid of special attention roof is also paid of special attention

55 References Q. Li, and et. al, “Distributed algorithm for guiding navigation across a sensor network”, MobiCom 03. Y.-C. Tseng, M.-S. Pan, and Y.-Y. Tsai, “A Distributed Emergency Navigation Algorithm for Wireless Sensor Networks”, IEEE Computers, Vol. 39, No. 7, July 2006, pp A Distributed Emergency Navigation Algorithm for Wireless Sensor Networks M.-S. Pan, C.-H. Tsai, and Y.-C. Tseng, “Emergency Guiding and Monitoring Applications in Indoor 3D Environments by Wireless Sensor Networks”, Int’l Journal of Sensor Networks, Vol. 1, Nos. 1/2, pp. 2-10, 2006.Emergency Guiding and Monitoring Applications in Indoor 3D Environments by Wireless Sensor Networks