This project will provide trial versions of the Elements Platform (a simple plug and play IoT platform for SME manufacturers) to manufacturers and monitor the subsequent adoption rate of the full Elements Platform.
This project, in collaboration with Upside Energy Ltd (UEL), will create a programme of research focused on data-driven battery energy storage degradation. and will deliver methods for estimating battery states that UEL will evaluate on their data set.
Supply chains are complex networks of independent companies, and full supply chain visibility is a common barrier to forming effective connections between suppliers. IoT can be utilised to improve information sharing to ensure accurate information is available throughout the supply chain
The issue of IoT data de-cluttering has been identified as a critical issue across university and industry partners. The main aim of this project is to identify methods to significantly improve understanding how IoT sensor data can reliably be integrated into system decision-making processes.
Landslides can pose a significant risk to life and economic disruption. The project aims to develop IoT integrated sensors with smart front and back processing using broadband satellite resilient connectivity, and incorporate data into existing business and decision making processes, as well as influence new processes.
Poor air quality causes millions of deaths across the world. This project will use air quality as a focus of integrating and adapting an already existing IoT system to collate a wealth of data sources for accurate monitoring and modelling.
The vision of the project is to build a network of organisations interested in IoT platforms and strategy. The project will focus on developing training in IoT and platform strategy for the network.
In this project, we aimed to explore IoT-enabled mechanisms that can be used to capture information on greenspace biodiversity specifically looking at sound-scape information. IoT-enabled mechanisms have the potential to significantly reduce the costs of data collection as well as leveraging citizen science, so allowing local governments to incorporate biodiversity into planning and design of green spaces.
To help develop prototypes and code that showcases the LoRaWAN network’s potential to campus community and local business, Pitch-In supported a 10-week student placement programme for engineering undergraduates from 22 June to 28 August 2020.
This project was to implement point of care (POC) testing devices in patients with severe mental illness in the community and to compare outcomes to similar patients managed by a team without access to these technologies.