We study a budget allocation problem for urban monitoring (e.g., pollution, litter etc.) using participatory sensing. The human participants and locations of phenomena to be sensed are modeled as Poisson point processes. The decision maker (e.g., city authority) has to decide the split of budget among strategies—advertisements to recruit participants, and providing rewards to those participants for their efforts in reporting the events. We propose and analyse three schemes for rewarding participants—equal, proportional and probabilistic. The probabilistic scheme exploits risk seeking behavior of participants, which is a typical human psychological behavior studied in the Prospect theory. Analytical and numerical study of the proposed schemes uncovers useful insights such as, for the equal reward scheme, advertisement for recruiting more individuals is preferable than increasing rewards for the recruited individuals. However, the opposite is true for the other two schemes.
['Siddhartha P. Sarma', 'Kundan Kandhway', 'Bhushan Kotnis', 'Joy Kuri']
Urban monitoring using participatory sensing: An optimal budget allocation approach