Arquitectura Adaptativa para CrowdSensing de Comunidades Eficientes
CROWDSENSING extends previous results of the consortium (UPM&UdG) achieved in the project MESC (DPI2013-47450-C2-R, 2014- 16) towards the integration of crowd-sensing with information traditionally managed in energy management systems (BMS/BEMS, WSN, Smartmeters, weather station, etc.) allowing a standardised access to energy and crowd-sensing data. Crowd-sensing is an emerging technology that allows improving observability of large spaces and their interaction with users and activities by exploiting smartphone sensing capabilities and aggregating conveniently.
Description
Thus, the general objective of CROWDSAVING is to provide a software infrastructure levering to monitor impact of user behaviour on the dynamics of energy/water distribution networks and energy intensive facilities. Crowdsensing enables the observation of social behaviour at different aggregation levels and requires specific methods and adapt variability of data streams to existing energy monitoring solutions. This general objective has been split into two subprojects addressing complementary objectives from two complementary points of view, software architecture and energy monitoring. Subproject 1, led by UPM team, addresses software engineering issues and aims enabling software architectures to support dynamic distribution networks, as an evolution from existing distribution networks. Subproject 2, led by UdG, focuses on new methods to monitor the impact of social behaviour on energy efficiency of power networks and facilities. Integration of architecture and monitoring methods dealing with the requirements of crowdsensing and allowing better observability of the impact of users behaviours on energy intensive spaces will be validated in two pilots at the premises of UdG and UPM; and, also, in collaboration with other agents that have demonstrated the interest for the results. The project has been organised in five work packages dealing with WP1: requirements definition, WP2: Architectural framework, WP3: Learning user/behaviour models based on crowd-sensing, WP4: behavioural energy monitoring, WP5: integration and validation (pilots), WP6: Coordination, Dissemination and Exploitation.
Project details
Code: TIN2016-79726-C2-2-R
Research areas: Services and Software Technologies
Status: Finished.
Project leader: Juan Garbajosa Sopeña; Jenifer Pérez Benedí
Members: Agustín Yagüe Panadero; Jessica Díaz Fernández; Norberto Cañas de Paz; Javier García Martín; Juan Sebastián Ochoa Zambrano; Jenifer Pérez Benedí; Juan Garbajosa Sopeña.
Start date:30-12-2016
End date:29-12-2019
Funding: Ministerio de Economía, Industria y Competitividad. Programa Retos Investigación 2016
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