Covid-19 has created an unprecedented situation of emergency lockdown worldwide that has impacted severely business both worldwide and in the UK. The Office of Budget Responsibility warns that the lockdown could wipe out up to 35% of our GDP. There is an enormous pressure on governments to ease the lockdown as soon as possible so to let business go back to normal. However, the return to normalcy will not be easy and some analysts warn that we should consider some forms of lockdown as the new normalcy for the next few years. In any case, this return will not be to business as usual in the short or medium term. Return to work will be in stages, with only part of the personnel back to work so to be able to impose distance measures - some analysts expect companies to command back to work about one third of the workforce for the first period. Companies will have the requirement to guarantee that their operations are compliant with any temporary or long term measure imposed by the government, including social distancing in the workplace and expedite identification of outbreaks. This will require new ways of organising works both in terms of physical spaces and in terms of work organisation. The goal of this project is to create a technology and methodology able to support these companies and organisations in this return process by providing support in (i) keeping the appropriate distance among employees while on premises; (ii) control communal areas (e.g. bathrooms, meeting rooms, etc.) to detect overcrowding; (iii) support planning of teamwork to minimise cross-contagion and (iv) ensuring that employees at risk (e.g. with existing conditions or of older age) are safeguarded. The technology is low cost, privacy preserving for the employees and of easy installation. It is based on a combination of mobile technologies and a limited number of beacons/detectors to be self installed on the premises. The solution provides an organisational dashboard to support control and support demonstrating compliance with the new regulations. In the project, we will build on our unique technology for tracking individuals and items. We will develop and expand it with a new range of capabilities, from new improved algorithms for Bluetooth colocation detection, to ultrasound social distance detection. We also plan expand our customer base and market by addressing higher education, energy, utilities, retail and manufacturers (including the food and automotive industries), as well as as well as other industries (eg. hospitality, events, cultural infrastructures) in the UK. Furthermore, international markets in the USA, Europe and Australia will also be targeted (with the same business verticals) to expand the size of the opportunity to Aeqora. We aim to commercialise a first product within 1-2 months after project end to be followed by a fully fledged product within 6-8 months.

"Papilloedema is the swelling of the optic nerve that leaves the eye to go to the brain. The brain is in a closed vault (the skull) therefore any lesion occupying space (tumour, bleeding) can press against the brain and cause death. Diabetic Retinopathy is one of the leading preventable causes of blindness in the world, providing a massive economic burden on both developed and developing countries worldwide. We will develop a smartphone based solution that will use an optical lens attached to the camera to carry out a full Ophthalmologist guided Optical examination, as well as image the back of a patient's eye to detect papilloedema and diabetic retinopathy. Hospital specialities based in central teaching hospitals are being increasingly asked to consult for patients in peripheral District Generals - remote consultation software capable of carrying out basic technical measurements would permit specialist doctors to cover greater catchment areas in a safe manner, improving outcomes for all concerned and avoiding unnecessary missed cases of these serious eye conditions. The automation of simple technical tasks with regards to the ophthalmological examination will also speed up consultations, and increase the number of patients that can be seen during routine screenings. For example, both diabetic retinopathy screening and the pre-school vision screening tests would benefit massively from the use of the proposed solution, and thereby significantly reducing the sight-loss burden in this country. Automated recognition of swollen optic nerves and diabetic retinopathy via a smartphone-based solution enhanced with machine learning capabilities also has the potential to save lives in A&E departments, general practitioners and optometrists across the country - and even world-wide."

The SmartBridge project aims to revolutionise the monitoring and maintenance of bridge infrastructure by developing an innovative knowledge-based digital platform that will enable the visualisation of bridges’ condition and degradation. These virtual models or twins will combine the multiscale 3D numerical models with sensor data collected and processed from real bridge infrastructure, incorporating operating environmental conditions and inspection history. Condition monitoring sensors including wireless accelerometers, displacement transducers, temperature sensors, strain gauges, barometers, hygrometers etc will be placed on bridges and data will be collected, processed and transferred to the digital twin, continuously resulting in a close to real digital twin of the bridge showing real-time conditions. Such a platform will allow bridge operators to predict failure and plan maintenance before incidents occur. It will reduce maintenance costs by 20% and downtime by 60%. The application of SmartBridge will include (1) Continous remote condition monitoring of bridges infrastructures (2) Risk-based inspection approach to perform intelligent maintenance operations, (3) A better understanding of lifecycle and degradation behaviour of bridges in different operating conditions.

Satellite imagery is an extremely useful source of data for emergencies and potential emergencies. It provides large scale surveillance of conditions, but now at spatial resolutions down to 0.5m. There are some 140 earth observing satellites in orbit, representing a huge virtual constellation of surveillance capability, expected to double in the current decade. However, in many cases these data are not being used effectively for emergency response because of a reactive approach in the industry to image acquisition. We propose to develop and define a pro-active approach to the tasking of satellite imagery in emergency response by the monitoring and interrogation of social media feeds as well as alerts from relevant organisations, so that the data can be rapidly accessed and exploited by emergency responders. The outcome of this proposed project will be a defined capability to optimise the use of satellite surveillance in a range of emergency situations. The market for this is considerable and currently under-served by satellites for a number of reasons which we intend to address technically and commercially.

Data is big and getting bigger ! Big in the sense of size, i.e. in ‘Volume, Variety and Velocity’, but also in the anticipated business value to be realised if these data can be harnessed, tamed and made to earn their keep. Realisation of this value is a big challenge however, calling upon scarce skills of the 'data scientist' which are as much routed in psychology and project management as in data analytics. This is especially the case when the end product quality variable of concern is potentially influenced by any contributory cause from several steps in a process chain, where expert knowledge tends to be fragmented.This project aims to produce a comprehensive tool box supporting project design, management and longer term deployment of process chain data analytics, embedding 'through process knowledge' via a collaborative project framework. The objective is to reduce reliance on ICT specialists and support a collaborative approach. The life cycle of this framework will start as a template for project definition and management, but will provide an organic deployable knowledge system, incorporating predictive analytics, to monitor and oversee ongoing production process in the future.

K-Spend focuses application of novel techniques to address issues in large scale procurement data aiding corporates in financial assessments and decision support. K-Spend brings technology allowing amalgamation of linked data and heterogenious flat file procurement data integrating distributed operational spend data with company and commodity data. This work delivers procurement information handling capabilities across medium and large scale organisations for analysis and decision support for procurement professionals.