SewerSnort: A drifting sensor for in situ Wastewater Collection System gas monitoring

  • Authors:
  • Jung Soo Lim;Jihyoung Kim;Jonathan Friedman;Uichin Lee;Luiz Vieira;Diego Rosso;Mario Gerla;Mani B. Srivastava

  • Affiliations:
  • UCLA CS, United States;UCLA CS, United States;UCLA EE, United States;KAIST KSE, Republic of Korea;Federal University of Minas Gerais, Brazil;UCI CEE, United States;UCLA CS, United States;UCLA EE, United States

  • Venue:
  • Ad Hoc Networks
  • Year:
  • 2013

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Abstract

Biochemical reactions that occur in sewer pipes produce a considerable amount of hydrogen sulfide gas (H"2S corrosive and poisonous), methane gas (CH"4 explosive and a major climate change contributor), carbon dioxide (CO"2 a major climate change contributor), and other volatile substances (collectively known as in-sewer gases). These toxic gases lead to contamination of natural environment, sewer pipe corrosion, costly operational expense, public safety issues, and legal disputes. In order to prevent biochemical reactions and to maintain healthy sewer pipes, frequent inspections are vital. Thus far, various schemes have been designed and developed to identify functional deficiencies in Wastewater Collection System (WCS). Nevertheless, the current inspection techniques are not for mapping the sewer gas concentration. In addition, because of such a harsh and hazardous environment a comprehensive sewer gases inspection has been prohibitively expensive. 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 down sewer pipeline, while the sensor float collects gas measurements along with location information of sampling points. At the end of the journey, the gas measurements are retrieved from the float and used to generate gas concentration to be used for maintenance 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.