Our project, Airspace Analytics Data Exchange, proposes to explore and design a solution that enables organisations, such as eVTOL (electric vertical takeoff and landing), commercial drones, vertiport operators, and more traditional organisations including local authorities, airfields and such, to have access to an online data exchange solution that could provide on-demand analysis of how UK airspace is used. This data and insight, in turn, will enable these organisations to better manage planning and operations relating to how their future services will interact with current and future airspace structures across the UK, thus aiding the UK's wider Net Zero and Jet Zero initiatives to progress. The project will be delivered by two innovative UK based SMEs, Plane Finder (who run an extensive network of ADS-B receivers across the UK, tracking aircraft and feeding their popular mobile app) and Emu Analytics (who's digital twin software is already used by the likes of British Airways, the Civil Aviation Authority and London Gatwick) to aid their operations.

Our project, MOBI, is a collaborative proposal focusing on two of the competition scope points, and bringing together two specialist UK-based micro-SMEs to develop it. 1. _sensor or sampler carrying platforms_: _Acua Ocean_ is an early stage UK business that is designing and developing future Marine Autonomous Surface Systems (MASS), vessels that are autonomous, zero-emissions, hydrogen fuelled, efficient and capable of carrying payloads of marine monitoring sensors, providing power and real-time backhaul of data for a range of marine biodiversity monitoring objectives. 2. _data analysis and visualisation systems_: project lead, _Emu Analytics_ is an award-winning _UK developer of real-time geospatial & temporal data analytics and digital twin software_, that has already been used in a number of adjacent sectors (including aviation, energy, transportation and telco). In 2021 the company was funded by the Geospatial Commission for its first foray into the maritime sector, adapting its technology to help the General Lighthouse Authorities understand the shipping navigational impact of future offshore windfarms. The MOBI project will set about to bring together these two elements of the broader needs of NCEA, by designing the standards by which data sourced from sensors on future Acua vessels, should be structured and exposed to facilitate the use of this data by advanced analytics and visualisation systems (in this case, Emu's digital twin technology). Project lead, Emu will additionally evolve and subsequently demonstrate how its software could be transitioned from adjacent industry sectors and applied to focus specifically on marine biodiversity data (and directly related data - for example offshore wind farms locations) , and leveraging Emu's prior experience in the analysis of offshore wind and shipping behaviours (given their direct impact on marine biodiversity). The output of this phase of the project will be a working demonstrator of Emu's technology, evolved and adapted to work with existing available open maritime data sets, and showcasing how future (or existing NCEA continuous data sources) could be easily integrated into it in later phases of work, combined with a data design for the management of data derived from future sensors aboard Acua's autonomous vessels.

MANTIS is a project focused on using geospatial data to address new and emerging challenges facing shipping and maritime navigational services within UK waters. The challenge is posed by the General Lighthouse Authority (and its sister organisation, Trinity House) who, under the jurisdiction of the Department for Transport, provide maritime aids to navigation services for the safety of all mariners, efficiency of maritime trade and protection of the marine environment throughout waters of the British Isles. The need is to better understand, and then predict, the impacts to shipping of the UK's stated aim to significantly increase off-shore wind farming capacity. This project will achieve this through the innovative analysis of ship movements and positions, throughout UK waters over periods of time, and utilising AI and machine learning technologies to identify evolving patterns of movement, leading to predictive outcomes for proposed future wind farm implementations. Lead applicant, Emu Analytics, is a young, UK-based micro-SME with extensive experience in creating innovative geospatial analytics and visualisation solutions designed for big, fast and real-time data. Its solutions are currently used extensively within the aviation sector, with notable users including IAG (British Airways), Heathrow and the Civil Aviation Authority, wherein the analysis of aircraft behaviours and patterns within UK airspace is undertaken, using big geospatial aircraft positioning data. MANTIS will seek to adapt, evolve and transfer this expertise and capability from aviation to maritime, utilising the comparable maritime sector ship positional data, and ultimately producing a powerful, commercial-grade solution that could be utilised by a broad range of public and private sector organisations.

Public description MANTIS is a project focused on using geospatial data to address new and emerging challenges facing shipping and maritime navigational services within UK waters. The challenge is posed by the General Lighthouse Authority (and its sister organisation, Trinity House) who, under the jurisdiction of the Department for Transport, provide maritime aids to navigation services for the safety of all mariners, efficiency of maritime trade and protection of the marine environment throughout waters of the British Isles. The need is to better understand, and then predict, the impacts to shipping of the UK's stated aim to significantly increase off-shore wind farming capacity. This project will achieve this through the innovative analysis of ship movements and positions, throughout UK waters over periods of time, and utilising AI and machine learning technologies to identify evolving patterns of movement, leading to predictive outcomes for proposed future wind farm implementations. Lead applicant, Emu Analytics, is a young, UK-based micro-SME with extensive experience in creating innovative geospatial analytics and visualisation solutions designed for big, fast and real-time data. Its solutions are currently used extensively within the aviation sector, with notable users including IAG (British Airways), Heathrow and the Civil Aviation Authority, wherein analysis of aircraft behaviours and patterns within UK airspace are undertaken, using big geospatial aircraft positioning data. MANTIS will seek to adapt, evolve and transfer this expertise and capability from aviation to maritime, utilising the comparable maritime sector ship positional data, and ultimately producing a powerful, commercial grade solution that could be utilised by a broad range of public and private sector organisations.

Planes, Trains (and Automobiles!), aka PTA is an innovative data-driven software solution led by two leading UK micro-SMEs, Emu Analytics and Plane Finder, and including as a third partner, Ferrovial (a major shareholder in several UK airports including Heathrow, Aberdeen, Glasgow and Southampton). The solution is designed to use data to analyse and predict delays across rail and air transport, to aid airports in safely and confidently managing passenger journeys to and from the airport, specifically by rail (the most sustainable means of reaching the airport) and using real-time location data from both aircraft and trains to better provide guidance and strategy that reduces the potential for passenger congestion, bottlenecks and dwells times at railways stations and airports. This capability will help airports adhere to recent Government guidance on managing multi-modal passenger journeys post COVID-19, and help restore passenger confidence in two transport sectors that have faced significant impact from the pandemic and lockdown, namely rail and commercial aviation. The project's three objectives are: * To enable Airport operators to more safely manage passengers who arrive / leave by rail in a post COVID-19 environment * To encourage passenger confidence and uptake of the most sustainable means to travel to the airport (rail) * To promote passenger confidence in the resumption of train and air travel, aiding two heavily COVID-19 impacted economic sectors. Only the two SMEs are seeking Innovate UK funding, as Ferrovial will cover all its costs of involvement itself, and will work with the project in aiding and implementing a trial of the solution within its airports. Emu Analytics is a leading provider of innovative real-time data analytics and visualisation software, providing its services to many large infrastructure, transport and smart city operators, whilst Plane Finder is one of the world's leading providers of real-time aircraft movement and position data, with multiple airlines and over 1 million monthly active users following aircraft movements on its mobile apps and website.

"WeatherSense+is a solution designed to allow the organisations responsible for key infrastructure to monitor, understand and predict the impacts of day-to-day and extreme weather on the ways in which real populations interact with infrastructure systems. It uses an innovative blend of big data analytics, real-time, historic and predictive data modelling and data from a variety of new and innovative sources including mobile phone networks, micro and macro weather sensors and a variety of open (and private) infrastructure / services data (such as transport and urban service operations). The platform collects, blends and analyses these data sets, and brings the derived insights to life through an interactive, visual web application, that will be made commercially available to relevant organisations, enabling them to react and plan for infrastructure impacts as a result of increasingly variable weather conditions in the UK."

A data, analytics and visualisation solution designed specifically to create valuable and actionable insights derived from Smart Meter data. It would offer insights and metrics to groups, organisations and the general public based on aggregated analysis of energy consumption patterns and their relation to geography, consumer type (residential, commercial), seasonality and more. All for the purpose of enabling comparable measures from which energy consumption inefficiencies can be addressed, and the subsequent improvements measured.