Innovative polymer-based composite systems for high-efficient energy scavenging and storage

InComEss seeks at developing efficient smart materials with energy harvesting and storage capabilities combining advanced polymer based-composite materials into a novel single/multi-source concept to harvest electrical energy from mechanical energy and/or waste heat ambient sources. The project will demonstrate its applicability in key sectors and applications, SHM and vehicle monitoring in automotive, aerospace and building, presenting the highest market potential.

Three cost-effective and green Εnergy Harvesting Systems (EHSs) configurations will be realized through the combination of high-performance piezoelectric (PE), thermoelectric (TE) and ThermoPiezoelectric (TPE) generators and monolithic supercapacitors (SCs) to power selected wireless sensors nodes to be implemented in different IoT scenarios for Structural Health Monitoring (SHM) in buildings and aircrafts and accurate location and monitoring of vehicles through GPS and MEMS sensing.

I-SENSE Group’s role in the project

The ISENSE Group of ICCS is participating in the project with the responsibility to integrate the WSNs with an IoT platform enabling the development and deployment of IoT applications across a variety of use cases (building, automotive and aeronautic). It will define the data flow architecture, data formats, communication protocols and services taking advantage from Edge Foundry, an open-source innovative framework that allows the simplified process of designing, developing and deploying IoT final solutions. Finally, it will develop the communication gateways to interconnect the wireless sensor nodes with the edge/ cloud (e.g. server). The gateway will retrieve information from the sensors via the low power wireless communication protocols (i.e. Bluetooth LE and LoRaWAN) and will translate the collected data to the appropriate format to feed the IoT services using a lightweight protocol (MQTT). Additionally, dashboards and front-ends tailored to each use case will be developed to visualize and monitoring historic data.