Urban Sensing Systems: Opportunistic or Participatory? Nicholas D. Lane Shane B. Eisenman Mirco Musolesi Emiliano Miluzzo Andrew T. Campbell Presented By: Pradeep Vaghela Outline Introduction Evaluation Model Related Work Conclusion Introduction • Urban Sensing Systems: large scale systems to sense the environment through making use of static or mobile sensors • “People Centric Sensing” – Using mobility of people and their mobile devices Introduction Reference:Mesh Networking , The rise of people centric Sensing- MetroSense Group Introduction Metrosence - A new wireless sensor edge network based on the concept of "people-centric sensing" at a large scale (campus, town, metropolies) Various projects: CenseMe-facilitate the sharing of "presence" information among friends. AnonySense project, we are working to ensure the security, trust, and privacy of people-centric data Architecture of People centric sensing system •Query submission-sensor type and sensing condition •Device selection- which resources to fulfill the query mobile phones or Wi-Fi access points •Sensor sampling- when to sample •Data analysis, sharing presentation Introduction Custodians of the mobile devices play vital role Participatory- active owner Opportunistic- passive owner Introduction- Participatory Sensing •Custodian involved at significant decision stages such as – what data to share, privacy mechanism •Example: DietSense( CENS-UCLA) Introduction- Opportunistic Sensing •Device is utilized whenever application requirements are met •Privacy and transparency are importance issues •Example : Pothole Petrol •Participatory or Opportunistic ? An evaluation model •Quantitative evaluation of the choice of the participatory model against opportunistic one •Notation. M – total no of devices in the system •Paccept_query •Puser_adapt •Pcontext_match •Phave_sensor An evaluation model Participatory Success Probability, Opportunistic Success Probability, Opportunist is better when, An evaluation model •Quantitative evaluation through Google street view like application Phave_sensor = 0.8( 80% of the cellphones have camera Pcontext_match = 838/(365*24*60) Pquery_accept = 0.3( contact rate using first call attempts Puser_adapt = 0.2 ( again using contact rate) An evaluation model.. An evaluation model.. An evaluation model.. (a) Opportunistic good when constituent model probabilities are in favor. Also performance degrade slowly (b) Increasing the number of devices only amplifies the positive aspect of the opportunistic approach Therefore, given uncertainty in the user population size and user participation probability supporting opportunistic sensing is well motivated. Related Work • • • Most system represent a middle ground Opportunistic- Cartel Urban Sensing project CENS demands more human intervention in the sensing loop. In DietSense , user takes photograph of the food Conclusion • • Two potential roles of sensor custodians in urban sensing systems are compared. Opportunistic sensing design more easily supports large scale deployments and application diversity. Critique and Questions? How reliable probabilities are ?