Multiple Access Communications Limited Public Funding

Contemporary IoT platforms typically adopt a cloud-based approach, with some offering optional backend installation at customer premises. This approach implies a requirement to transmit, process and store all data points in the Cloud or user backend. This design pattern is unsustainable due to the volume of data generated, especially in the case of applications that rely on data collected by battery-powered, resource-constrained devices deployed at massively large scale. Pushing some of the computation to the Edge and exploiting distributed AI can alleviate some of the burden from cloud infrastructures, and therefore decrease latency and improve scalability. However, this results in new challenges and a need for further industry research. How can we compute energy-efficiently at the Edge? How do we assure the security and resilience of such distributed systems, especially in the case of applications that target the digitisation of critical infrastructures? SYNERGIA will devise, develop and demonstrate a novel secure-by-design, endpoint-to-core IoT platform for large-scale networks of low-power resource-constrained devices. The platform will provide users with distributed processing capability at the Edge as a service. Security issues will be addressed at all platform tiers: resource-constrained devices, Edge and backend. To achieve this, we will undertake industry R&D on scalable, secure configuration management and control of IoT systems; secure connectivity for battery-powered resource-constrained devices; edge-based AI for cyber security of IoT systems. SYNERGIA will leverage an edge platform currently under development by one of the project partners. It comprises a collection of interconnected edge nodes with sensing capabilities and a backend that enables end users to develop and deploy applications with distributed edge processing as a service. Project outcomes will be showcased in an integrated fashion at two demonstration events. The project is led by a worldwide provider of secure IoT networks (Toshiba). The team consists of UK experts in secure communications for IoT devices (Ioetec, SME); a start-up in secure configuration management and control of IoT systems (Configured Things, SME); a UK leader in industrial AI technology (Smartia, SME). Developing an application use-case and leading engagement with end users will be Multiple Access Communications Limited (MAC Ltd, SME), with a track record of designing IoT solutions in several sectors including public safety, infrastructure monitoring, smart buildings and assisted living. The University of Bristol brings world-leading expertise in IoT networking, cybersecurity and distributed AI.

Tag & track provides the controls needed for effective implementation of industrialised construction activities, leading to certainty of outcome & reduced costs. There are a number of tag/track approaches (RFID/Bluetooth enabled, QR, Barcodes) that can be used to collect real-time data on the status/location of a component during the construction and life of a facility. To date the use of tag/track in construction has been restricted by cost of hardware & limited supply chain integration. However, its use in combination with 4D-BIM will allow progress on projects to be monitored against plan, enabling efficiency improvements (eg addressing scheduling issues that would otherwise cause delays) with 10% reductions in programme time targetted. The project will develop a solution for real-time tracking of component status during manufacture which can utilise different tag/track approaches. It will also develop a ‘schema’ to capture data from multiple supply chains in a standard format for integration into 4D BIM models. Outputs will be piloted in supply chains for real projects. Implementation will accelerate uptake of BIM throughout supply chains, contributing to an estimated 20% efficiency improvement.