Designing Wireless Sensor Networks as a Shared Resource for Sustainable Development

Abstract

Wireless sensor networks (WSNs) are a relatively new and rapidly developing technology; they have a wide range of applications including environmental monitoring, agriculture, and public health. Shared technology is a common usage model for technology adoption in developing countries. WSNs have great potential to be utilized as a shared resource due to their on-board processing and ad-hoc networking capabilities, however their deployment as a shared resource requires that the technical community first address several challenges. The main challenges include enabling sensor portability -the frequent movement of sensors within and between deployments, and rapidly deployable systems -systems that are quick and simple to deploy. We first discuss the feasibility of using sensor networks as a shared resource, and then describe our research in addressing the various technical challenges that arise in enabling such sensor portability and rapid deployment. We also outline our experiences in developing and deploying water quality monitoring wireless sensor networks in Bangladesh and California.

The impact of agricultural activities on water quality: A case for collaborative catchment-scale management using integrated wireless sensor networks

“…Although sensor nodes have become inexpensive, the high cost of some sensors (e.g. ammonium) is a major barrier for dense deployment of WSNs (Ramanathan et al, 2006).…”

“…WSNs have been successful in understanding the trends of nutrients and contaminants fluxes owing to non-point source activities in a catchment. However, this understanding is limited as it can currently only use small-scale, localized and specific measurements at rivers, lakes, dams and groundwater reservoirs (Ramanathan et al, 2006, Le Dinh et al, 2007, Zennaro et al, 2009, Papoutsa et al, 2010, Seders et al, 2007, Regan et al, 2009. These water resources receive contaminants as a result of activities up in the catchment, thus providing insufficient information for quantifying explicit responsible activities.…”

“…Furthermore, these frequencies are unsuitable for underground WSNs, which are ideal for non-invasive soil monitoring, as they suffer data losses due to soil water content Stuntebeck, 2006, Li et al, 2007). In an experiment, sensor and link failures were handled by 1) identifying patterns in data to indicate sensor failure and 2) using decision trees based on data flow models to identify link failure (Ramanathan et al, 2006). Top level concepts and protocols are applicable without any changes but care is needed for practical deployment and it may be that certain applications require a significant rethink of the communication requirements, which may not be addressed by current off-the-shelf solutions.…”

Know Thy Sensor: Trust, Data Quality, and Data Integrity in Scientific Digital Libraries

“…This group has surveyed existing approaches to data integrity, implemented both rule-based and statistical learning algorithms, and initiated data integrity experiments, either leveraging existing CENS field deployments or designing original experiments. Members of this group are routinely included in pre-deployment design discussions and consulted during post-deployment analysis, for applications as diverse as aquatic sensing [18], a soil observing system for examining CO2 flux [19], and a short-term deployment in a rice paddy in Bangladesh to study groundwater arsenic content [20].…”

Model-based monitoring for early warning flood detection

“…The project installed 2 nodes for 1.5 years in a highdesert farm and 24 nodes in the UCLA Botanical Gardens for 3 months. Finally, a 12-node system was installed in a Bangladesh rice paddy for 2 weeks to measure nitrate, calcium, and phosphate (this experiment also described in [29]). These nodes used 433 MHz communication systems to share the data measured and a base station sent the data for offline analysis.…”