Internet of Things <strong>Success</strong> <strong>Stories</strong> Series #3 IoT-based Monitoring and Management Approach for Smart Infrastructures This gap has been calculated obtaining a reduction of 18.28% of the consumed energy proving the benefit of using our platform based on IoT. Regarding the agricultural scenario, our platform is able to gather the information transmitted wirelessly by the sensors deployed in the field crop. Actually, the following graphs corresponding to Figure 8 shows the information related to humidity and conductivity measured by the deployed sensors. This information has been analyzed by agronomic engineers to estimate the amount of water needed to irrigate the field crop in order to make a more efficient irrigation process by using, in a next iteration, this platform wasting the minimum amount of water as well as obtaining the highest quality in the barley planted. These two heterogeneous scenarios proved the success of the platform based on IoT by OdinS, as well as its communication model being a suited platform for managing and monitoring smart infrastructures. 5. Acknowledgments Figure 8. Humidity and conductivity information gathered by the deployed sensors This work has been partially sponsored by European Commission through the FP7-SMARTIE-609062 project 6. References Berglund, L., Mathematical models for predicting the thermal comfort response of building occupants. ASHRAE Transactions, vol. 84, no. 1, pp. 735-749, 1978. Callaghan, V., Clarke, G., Colley, M., Hagras, H., Chin, J., Doctor, F., Inhabited intelligent environments, BT Technology Journal, vol. 22, no. 3, pp. 233-247, 2004. EN 15251:2006. Indoor Environmental Input Parameters for Design and Assesment of Energy Performance of Buildings – Addressing Indoor Air Quality, Thermal Environment, Lighting and Accoustics, Centre Europeen de Normalisation, 2006. Habitat, U.N. 2010. State of the world’s cities 2010/2011: Bridging the urban divide. Nairobi, Kenya: UN Habitat. Jones, A. The Future of EU Research : The Innovation Union and European Innovation Partnerships. In Research Support Blog, 2011. Moreno-Cano, M., Zamora-Izquierdo, M., Santa, J., Skarmeta, A. F., An indoor localization system based on artificial neural networks and particle filters applied to intelligent buildings. Neurocomputing, vol. 122, pp. 116-125, 2013. Perera, C., Zaslavsky, A., Christen, P., Georgakopoulos, D., Sensing a service model for smart cities supported by Internet of Things, In Trans. Emerging Tel Tech., 2013. Zamora-Izquierdo, M. A., Santa J., Gomez-Skarmeta, A. F., An integral and networked home automation solution for indoor ambient intelligence, Pervasive Computing, IEEE, vol. 9, no. 4, pp. 66-77, 2010. Internet of Things • <strong>Success</strong> <strong>Stories</strong> 66 SERIES #3 - November 2015
Series 3 November 2015 Editor : Philippe Cousin This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 609024
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