Urban Sensing Systems: Opportunistic or Participatory?

Nicholas D. Lane

Shane B. Eisenman

Mirco Musolesi

Emiliano Miluzzo

Andrew T. Campbell

Presented By:

Pradeep Vaghela

OutlineIntroductionEvaluation ModelRelated WorkConclusion

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 ?