Cloud monitoring kit for citizen science
Reference persons GIACOMO CHIESA
External reference persons Francesca Fasano, Paolo Grasso
Description This thesis proposal is part of H2020 PRELUDE citizen science and education activities and candidate student(s) will be asked to develop communication and cloud storage solutions for multi IoT sensor kits to be distributed in several Piedmont buildings. Kits are expected to be based on Arduino and Raspberry usign local wi-fi for data transmission. Node may be independent (single node + wi-fi communication) or connected (optional action) by developing a LoRaWAN gateway. Candidate(s) is/are asked to develop both or one of the following issues: i. a server facility for collecting data from registered nodes, store them and allow simple visualisation; ii. updates or re-development of sensor nodes to define stable solutions to be potentially passed to PCB production. Candidate(s) will work for the definition and tests of communication logics between local nodes and between nodes and cloud facilities, the development of basic cloud platform and simple dashboards, the assembling/organising single monitoring nodes (prototypes) to support above testing actions. The definition of specific sensors to be integrated has been already partially established by previous tests, but may be improved.
The work is part of the citizen science and education activities of the H2020 project PRELUDE and may benefit from the possibility to test and install some developed kits in different buildings in the Piedmont Region (schools, residential, ...) and results will be discussed with project industrial and academic partners. Potential high quality results may benefit from dissemination activities. The final version of the cloud storage and platform is expected to be implemented in the server facility of the research group.
Required skills Candidate(s) need to have knowledge on electronics and sensoring, IoT, API management, communications, small server development.
Notes La tesi puņ essere svolta eventualmente in italiano, se ammesso dallo specifico corso di laurea.
Deadline 19/10/2022 PROPONI LA TUA CANDIDATURA