SIMPLIFAI pronounced simplify. The project aims to address the challenges surrounding the complex interaction between environmental, social and economic aspects of urban transport movements. It will do this using advanced computing techniques to simplify the interaction between transport managers and users of transport networks. The project will build on state of the art transportation management systems and cutting edge research to produce a new form of transportation management to meet the urban transport challenges of the mid 21st Century. The project is led by KAM Futures and supported by industrial partners partners BT, Infohub and KAM Futures, with technical academic expertise from The University of Huddersfield. The end customer is Transport for Greater Manchester. The project aims to build on the Innovate UK funded innovation voucher between KAM Futures and University of Huddersfield and the technical feasibility study undertaken in the Innovate UK funded project SimplifAI. The technical innovation is a new form of AI planner that can be deployed in a hyper cat enabled internet of things environment. The project combines environmental data sets with the data collected by the local authority to increase the resilience, quality of life and economic performance of the urban area using new ways of reasoning with and combining data

SIMPLIFAI - (pronounced simplify) - The project aims to address the challenges surrounding the complex interaction between environmental, social and economic aspects of urban transport movements. It will do this using advanced computing techniques to simplify the interaction between transport managers and users of transport networks. The project will build on state of the art transportation management systems and cutting edge research to produce a new form of transportation management to meet the urban transport challenges of the mid 21st Century. The project is led by KAM Futures and supported by industrial partners partners BT, Infohub and KAM Futures, with technical / academic expertise from The University of Huddersfield. The end customer is Transport for Greater Manchester. The project aims to build on the Innovate UK funded innovation voucher between KAM Futures and University of Huddersfield and the technical feasibility study undertaken in the Innovate UK funded project SimplifAI. The technical innovation is a new form of AI planner that can be deployed in a hyper cat enabled internet of things environment. The project combines environmental data sets with the data collected by the local authority to increase the resilience, quality of life and economic performance of the urban area using new ways of reasoning with and combining data

SIMPLIFAI - (pronounced simplify) - The project aims to address the challenges surrounding the complex interaction between environmental, social and economic aspects of urban transport movements. It will do this using advanced computing techniques to simplify the interaction between transport managers and users of transport networks. The study will build on state of the art transportation management systems and cutting edge research to produce a new form of transportation management to meet the urban transport challenges of the mid 21st Century. The project is a business led collaborative research project with industry partners BT, Infohub and KAM Futures, with technical / academic expertise from The University of Huddersfield. The challenge owner is Transport for Greater Manchester. The project combines environmental data sets with the data collected by the local authority to increase the resilience, quality of life and economic performance of the urban area using new ways of reasoning with and combining data.

The Ebbs and Flows of Energy Systems (EFES) project looks to develop a grid balancing platform to provide electrical support to the national grid during peak energy demand times, such as evenings. The project will achieve this through development of a virtual power plant (VPP), a cloud based 'power plant', capable of utilising dispirate electricity storage assets through a software package and controlled by utility providers. Supporting technology will also be developed through this project, including; a building energy management system (BEMS) for domestic and commercial building control functionality to support the VPP, domestic battery storage (BS) to store electricity during low tariff times for re-distribution during peak demand and vehicle-to-grid (V2G) electric vehicle (EV) charging capability to enable EVs to act as a battery store. The VPP will use current and historical consumer data to caculate the available battery provision to the national grid. The result of this support is a reduced requirement for rapid response services in the way of fossil fuel power plants, generating both a economic and environmental savings.

The growth of open data in the transport section has created possibilities for developing new transportation management information and control systems. The use of data analytics and learning algorithms plays an important role in the development of these new systems. This project will apply those techniques to sources of open data in the transport sector to scope a proposal for a new form of autonomic transport system.

This feasibility study will develop the concept of an Ebb and Flow Energy System (EFES) for a building or community based location. The proposal is based on three components. Firstly the Virtual Power Plant (VPP) at an aggregate level combining energy generation from a number of sources with the potential to become positive energy buildings having the ability to satisfy its own energy needs (thermal and/or electric) and contribute excess power to the community. Secondly electric vehicles with a vehicle to grid capability and smart metering to allow the ebb and flow of energy between the grid, the virtual power plant, the electric vehicles and the end use devices. The third element is the new business models for implementation and operation. The positive energy building concept becomes technically and economically feasible if extending its boundary to groups of buildings, campuses, communities (aggregators). While the proposal is technically innovative it also requires a new form of business model to enable it to develop into a market ready solution. The feasibility study will identify approaches to address the technical issues already noted and engage with appropriate stakeholders and collaborative research partners to develop business models for partic