Personal area networks: near-field intrabody communication
IBM Systems Journal
Dynamic Power Management in Wireless Sensor Networks
IEEE Design & Test
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
From Smart Homes to Smart Cities: Opportunities and Challenges from an Industrial Perspective
NEW2AN '08 / ruSMART '08 Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking
LTE, The UMTS Long Term Evolution: From Theory to Practice
LTE, The UMTS Long Term Evolution: From Theory to Practice
Design of a solar-harvesting circuit for batteryless embedded systems
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Smart cities at the forefront of the future internet
The future internet
A green wireless sensor network for environmental monitoring and risk identification
International Journal of Sensor Networks
A Maximum Likelihood Approach to Continuous Speech Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 20th ACM international conference on Information and knowledge management
"I'm eating a sandwich in Glasgow": modeling locations with tweets
Proceedings of the 3rd international workshop on Search and mining user-generated contents
A comparison of web robot and human requests
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Hi-index | 0.00 |
Smart cities are powered by the ability to self-monitor and respond to signals and data feeds from heterogeneous physical sensors. These physical sensors, however, are fraught with interoperability and dependability challenges. Moreover, they also cannot shed light on human emotions and factors that impact smart city initiatives. Yet everyday, millions of city dwellers share their observations, thoughts, feelings, and experiences about their city through social media updates. This paper describes how citizens can serve as human sensors in providing supplementary, alternate, and complementary sources of information for smart cities. It presents a methodology, based on a probabilistic language model, to extract the perceptions that may be relevant to smart city initiatives from social media updates. Geo-tagged tweets collected over a two-month period from New York City are used to illustrate the potential of social media powered human sensors.