Distributed sensing from energy harvesting mobile devices

Contact names: Dr. Michele Rossi

Institution: University of Padova

Application deadline:

Description: we will study social and distributed sensing strategies from EH mobile devices, to orchestrate when and where to sample, i.e., which mobile devices should report their readings. Also, we will study dedicated compression algorithms for complex spatio-temporal signals to allow their accurate reconstruction through the collection of a minimal amount of information.

Expected Results: define dedicated spatio-temporal algorithms for social sensing; these will result from the combination of compressive data gathering, energy saving strategies, adaptive sampling. Several use cases will be identified; focusing on the collection of data in smart cities (pollution, traffic level, acoustic noise level, etc.) and smart health systems.

Mobility Schedule: The ESR will be mainly at University of Padova. After 20 months the candidate is expected to spend 8 months at World Sensing to investigate distributed sensing strategies and check their performance with data sets from large IoT installations for smart cities. Access real sites and experiment with IoT technology.

Requirements of the candidate:

  • At the time of recruitment, the applicant must not have lived in Italy for more than 12 months in the previous 36 months

  • A Master degree in Telecommunications, Computer Science or equivalent

  • Once selected by the SCAVENGE consortium for the ESR positions, the applicants must apply for PhD studentship at University of Padova.

  • Knowledge on mobile networks, sensor networks, big data

  • Knowledge on energy systems and management

  • Ability and motivation to conduct high-quality research, including publishing the results in relevant venues

  • Strong programming skills (e.g. C/C++, Java, Python).

  • Working experience in the areas of Mobile Networks, Sensor Networks, Smart Grid, Energy Harvesting, Big Data management, Cloud computing is an advantage.

  • Knowledge on Optimization Theory is an advantage.

  • Knowledge on IoT devices is an advantage.

  • Very good communication skills in oral and written English.

  • Open-mindedness, strong integration skills and team spirit.