WiFiScout: A Crowdsensing WiFi Advisory System with Gamification-based Incentive
Fang-Jing Wu, Tie Luo

TL;DR
WiFiScout is a crowdsensing system that uses gamification to motivate users to share WiFi hotspot quality data, helping smartphone users find good WiFi spots in smart cities.
Contribution
It introduces a novel gamification-based incentive scheme for crowdsensing WiFi quality data collection in urban environments.
Findings
System successfully implemented on Android
Collected city-wide WiFi quality data from real users
Gamification increased user participation
Abstract
As mobile crowdsensing techniques are steering many smart-city applications, an incentive scheme that motivates the crowd to actively participate becomes a key to the success of such city-scale applications. This paper presents a crowdsensing WiFi advisory system called WiFiScout, which helps smartphone users to find good quality WiFi hotspots. The quality information is defined in terms of user experience and hence the system requires users to contribute information of their experience with WiFi hotspots. To motivate people to contribute such information, we design and implement a gamification-based incentive scheme in WiFiScout. It allows a user to "conquer WiFi territories" by becoming the top contributor for WiFi hotspots at different locations. The contribution is based on the diversity and amount of data a user submits, for which he will be rewarded accordingly. WiFiScout has been…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
