Monte Carlo localization: efficient position estimation for mobile robots
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Node Localization Using Mobile Robots in Delay-Tolerant Sensor Networks
IEEE Transactions on Mobile Computing
PIPENETa wireless sensor network for pipeline monitoring
Proceedings of the 6th international conference on Information processing in sensor networks
Low-power high-accuracy timing systems for efficient duty cycling
Proceedings of the 13th international symposium on Low power electronics and design
An experimental look at RF propagation in narrow tunnels
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
MoteTrack: a robust, decentralized approach to RF-Based location tracking
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
SPAMMS: a sensor-based pipeline autonomous monitoring and maintenance system
COMSNETS'10 Proceedings of the 2nd international conference on COMmunication systems and NETworks
Identifier based graph neuron: a light weight event classification scheme for WSN
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Mapping hidden water pipelines using a mobile sensor droplet
ACM Transactions on Sensor Networks (TOSN)
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Biochemical activities in sewer pipes generate various volatile substances that lead to several serious problems such as malodor complaints and lawsuits, concrete and metal corrosion, increased operational costs, and health risks. Frequent inspections are critical to maintain sewer health, yet are extremely expensive given the extent of the sewer system and the "unfriendliness" of the environment. In this paper we propose SewerSnort, a low cost, unmanned, fully automated in-sewer gas monitoring system. A sensor float is introduced at the upstream station and drifts to the end pumping station, collecting location tagged gas measurements. The retrieved SewerSnort provides an accurate gas exposure profile to be used for preventive maintenance and/or repair. The key innovations of SewerSnort are the fully automated, end-to-end monitoring solution and the low energy self localizing strategy. From the implementation standpoint, the key enablers are the float mechanical design that fits the sewer constraints and the embedded sensor design that matches the float form factor and complies with the tight energy constraints. Experiments based on a dry land emulator demonstrate the feasibility of the SewerSnort concept, in particular, the localization technique and the embedded sensor design.