|M.Sc Student||Sosko Shay|
|Subject||Densifying Static Geosensor Weather Networks via|
Crowdsourcing of Mobile Sensor Observations
|Department||Department of Civil and Environmental Engineering||Supervisor||Dr. Sagi Dalyot|
|Full Thesis text|
Static geosensor networks (also referred to as WSN - Wireless Sensor Network, or ESN - Environmental Sensor Network) are comprised of stations with sensor devices required for various applications for monitoring phenomena in a geographic perimeter. Networks are deployed in a large area for the purpose of collecting data from the surrounding environment with the capacity of transmitting it. Early warning systems for disaster management usually rely on static geosensor network that monitors a predetermined stationary area for providing hazardous warning; nevertheless, static geosensor networks show some limitations, in terms of insufficient coverage, low density, lack of mobility, limited power source and budget constraints.
In recent years, the use of Volunteered Geographic Information (VGI) has emerged as a working methodology for retrieving real-time data in disaster areas. VGI is a subset of crowdsourcing paradigm, a working premise in which user-generated information is gathered and shared by individuals participating voluntarily in a specific task. Using VGI methodologies, limitations related to the use of static geosensor network can be reduced, e.g., coverage and density of the network can be expanded using real-time user generated observations (negating the cost limitation). Moreover, the location of the reporters varies in time, hence making the network dynamic and flexible, allowing disabled sensor (damaged/blinded/without power source) to be replaced by real-time data generated voluntarily by nearby citizens - and so forth.
The research objective is to investigate, examine and prove the feasibility of using crowdsourced user-generated sensor data for the creation of a unified geosensor network, which will be used for densification of static geosensor network. The research hypothesis is that this model will not only maintain the static geosensor network capabilities but also augment it by overcoming certain abovementioned shortcomings. The case study of the research is weather data: crowdsourced volunteered weather data will be collected and used for improving coverage, resolution and reliability of weather stations network, resulting in a more densified geosensor network. Although the research case study is weather data, the proposed standpoint of using user-generated sensor data collected via crowdsourcing process for augmenting limitation of static geosensor networks can be implemented as a general solution, enhancing their capabilities.
Accomplishing those objectives was done by collection of crowdsourced weather data using mobile sensor, in different scenarios, in respect to reference data. The collected data was analyzed for determining statistical preferences, with and without post-processing. Stabilization algorithm was developed for determining the reliability, therefore usability of the crowdsourced weather data in real-time without the need of reference data. Another algorithm was developed for filtering irrelevant or erroneous VG weather data contributed by crowdsourced weather map, which was used for simulation and assessment of using VG weather data for densifying geosensor network.
The implementation of the proposed methodology was found to be sound and robust, delivering with results which satisfied the objectives of the research and proved the feasibility of using crowdsourced weather data for the augmentation of static geosensor networks, validating the assumptions and hypothesis made, thus fulfilling the research purpose.