Feedforward backpropagation artificial neural networks on reconfigurable meshes
Future Generation Computer Systems - Special issue: Bio-inspired solutions to parallel processing problems
Digital Image Processing
Automatic Text Location in Images and Video Frames
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Intelligent light control using sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
Countersniper system for urban warfare
ACM Transactions on Sensor Networks (TOSN)
The design and evaluation of a hybrid sensor network for Cane-Toad monitoring
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
CarTel: a distributed mobile sensor computing system
Proceedings of the 4th international conference on Embedded networked sensor systems
The design and evaluation of a mobile sensor/actuator network for autonomous animal control
Proceedings of the 6th international conference on Information processing in sensor networks
Health monitoring of civil infrastructures using wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Wireless Sensor Networks for Home Health Care
AINAW '07 Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02
Automatic Detection and Classification of Traffic Signs
WIAMIS '07 Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services
Protocols and Architectures for Wireless Sensor Networks
Protocols and Architectures for Wireless Sensor Networks
The BikeNet mobile sensing system for cyclist experience mapping
Proceedings of the 5th international conference on Embedded networked sensor systems
Detecting and reading text in natural scenes
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Finding the best-fit bounding-boxes
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Mobeyes: smart mobs for urban monitoring with a vehicular sensor network
IEEE Wireless Communications
Detection of text on road signs from video
IEEE Transactions on Intelligent Transportation Systems
Automatic detection and recognition of signs from natural scenes
IEEE Transactions on Image Processing
Are you contributing trustworthy data?: the case for a reputation system in participatory sensing
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Wireless sensor deployment for collaborative sensing with mobile phones
Computer Networks: The International Journal of Computer and Telecommunications Networking
A survey on privacy in mobile participatory sensing applications
Journal of Systems and Software
GeoCrowd: enabling query answering with spatial crowdsourcing
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Towards a generic framework for trustworthy spatial crowdsourcing
Proceedings of the 12th International ACM Workshop on Data Engineering for Wireless and Mobile Acess
Hi-index | 0.00 |
It is an undeniable fact that people want information. Unfortunately, even in today's highly automated society, a lot of the information we desire is still manually collected. An example is fuel prices where websites providing fuel price information either send their workers out to manually collect the prices or depend on volunteers manually relaying the information. This paper proposes a novel application of wireless sensor networks to automatically collect fuel prices from camera images of road-side price board (billboard) of service (or gas) stations. Our system exploits the ubiquity of mobile phones that have cameras as well as users contributing and sharing data. In our proposed system, cameras of contributing users will be automatically triggered when they get close to a service station. These images will then be processed by computer vision algorithms to extract the fuel prices. In this paper, we will describe the system architecture and present results from our computer vision algorithms. Based on 52 images, our system achieves a hit rate of 92.3% for correctly detecting the fuel price board from the image background and reads the prices correctly in 87.7% of them. To the best of our knowledge, this is the first instance of a sensor network being used for collecting consumer pricing information.