Algorithm A1. Modified algorithm for region identification and grouping of participants based on clusters using K-means with node S

1. Set S: node for participant’s smartphone

2. Set Lat: Latitude

3. Set Long: Longitude

4. Set T: Time

5. Set SA: Sub-arealist = [SA1, SA2, SA3,…, SAn]

6. Set Dist: Distance

7. K: Clusters of nodes into sub-areas

8. TWindow: Time T, set for the location of nodes a threshold

9. Start

10. Input S: Output (Lat, Long, Time)

11. Input Sub-area list [SA1, SA2, SA3,…, SAn, Lat, long, T]

12. Output S clusters in Sub-areas, SAn

13. While S is ready do

14. For each S for participant in Sub-Arealist do

15. Set locationUpdateWindow

16. Set minT i.e., for location manager minimum power consumption with minT

Milliseconds between location update to reserve power

17. Set minDist: as location transmission in case device moves using minDistance

meters

18. TDifference = location.getT( )- currentbestlocation.getT( )

If TDifference > TWindow then participant (node) have moved and transmit

the new location into a Crowd Controller Station (CCS) based on timestamp

change

19. If (Lat, Long) in location context with Sub-arealist SAn are the same,

clusters set K using Dist between the nodes S

20. Group S into SA1, SA2, SA3,…, SAn clusters

21. Crowdcount = S + 1

22. End If

23. End If

24. End For

25. End While

26. End