Public Funding for Vortex Iot Limited

Vortex IoT is an award-winning Wales based SME heading up a consortium that also includes Network Rail and Transport for Wales, Kelos Amey, Balfour Beatty. The company has a proven record in product development and has assembled a highly qualified team of Engineers who are specialist Internet of Things (IoT), wireless mesh networks and Artificial Intelligence (AI). Whilst its partners are a prime rail contractor and integrator and Network Rail Infrastructure respectively (Railway asset owner/ customer). There is an increasing demand for high availability of rail infrastructure and rolling stock assets for rail passenger journeys and freight customers. Remote Condition Monitoring (RCM) of rail infrastructure is essential to maximise the reliability and maintainability of the rail network and is a key enabler for achieving the goal of 'Minimal Disruption and Delay' set by Network Rail’s Capability Delivery Plan. This funding bid is focussed on securing additional funds to accelerate a ‘first mover’ RCM solution to market. The proposed project - RODIO®-TSM (Railway Optical Detection of Obstructions and Intrusions-Tunnel and Station Monitoring) - will deploy and integrate 18 devices in two live rail locations: a live 1.2km rail tunnel and 200m of its either entrance at Melton offered by NRI and a live train station in South Wales (Bargoed) with 200m station area and 100m urban tunnel. The project will user test the intrusion/obstruction detection capability of the LiDAR sensor network, that are wirelessly connected to RODIO edge gateway where the sensor fusion and AI engine resides to process the data and then results (e.g. Notifications, Threat level, …) are pushed to Network Rail Telecom (NRT) cloud server and ubiquitous IP Network. The system uses data fusion and Deep Learning classifiers to identify intrusion and obstruction types and severities aiming for high recall (sensitivity) and high precision against false alarms. This system can accurately detect, differentiate and classify (a) Intrusions – Human and Animal movements (b) Obstructions – Rock fall, tree fall, brick fall, debris fall, (c) Geotechnical asset failures – localised rapid earthworks, flooding, landslides and then sends real time situational alerts to the rail control centre to prompt further investigation as an advisory system. The NRl Product Acceptance Framework defined by Rail Industry Readiness Level (RIRL) is a vital indicator of our product maturity. The RODIO-TSM project will advance the current position of the RODIO® product to RIRL8.

no public description

HyperLocal Air Quality Monitoring for Smart Cities (HyLAQ)

"PARSER is an industrial research project developing a scalable solution to the combined problems of urban parking and air and noise pollution. Cars travelling at low speeds while searching for parking spaces contribute greatly to congestion and pollution. According to the British Parking Association drivers take an average 5.9 minutes searching for a parking space adding up to an estimated 4 days per year. On average 40% of UK Councils' revenue is generated through parking and each council is also being pushed heavily to demonstrate environmental policy monitoring tools as our cities and urban areas will witness major change and population shift over the coming 20 years. PARSER is a product we feel hits a genuine urban need that can also enable new and sustainable urban business models. There is an inherent and pressing need to build new energy, transport and urban systems to meet societal challenges such as a growing and ageing population, urbanisation and the need to reduce carbon emissions. _With_ _more than 70% of people estimated to be living in urban areas by 2040, city infrastructure and design is going to need to drastically change to better support its citizens._ Emerging internet-of-things (IoT) technologies can offer the ability to sense parking occupancy, traffic flows, congestion and air quality on a hyper-local scale. However, there are significant challenges to combine the technologies and develop the machine learning classifiers to interpret the data. The project aims to develop a LiDAR based parking monitoring solution coupled with air and noise pollution sensors. Together the consortium partners, Vortex IoT, BT, Swansea University and Swansea Council, will develop and deploy prototype sensors to test sites in the Swansea City region. Vortex IoT will take the lead on developing the sensors and wireless networks, Swansea University will focus on machine learning while Swansea Council will provide installation services and access to BT's on-street WIFI across areas of the city centre as designated for pilot. This project will deliver significant export led growth, a substantial ROI, increased employment and further opportunity for R&D investment for all consortium partners."

RODIO is an industrial research project developing a scalable solution to address the complex challenges of remote condition monitoring (RCM) of rail tracks. The RCM challenges identified by Network Rail include tree fall, rock fall, trespassing, animal intrusion, landslide and subsidence. The emerging internet-of-things (IoT) technologies can offer low-power and remote sensing and data communication for the RCM problem. However, technical and scalability challenges include powering and maintenance of sensors and wireless connectivity in network wide, remote and harsh environment. The project aims to develop near real-time detection and identification of intrusions and obstructions on rail tracks. The system performance will be analysed and evaluated through a live pilot deployment in TATA Steel Port Talbot (Wales). Exploitation and deployment of low-power IoT solutions, artificial intelligence and edge computing on the existing rail network will deliver state-of the-art RCM systems which will be beneficial to the UK rail infrastructure, train operators, passengers and freight customers. The project team including IOTICS, Vortex-IOT, Fincore, TATA Steel UK and Network Rail Infrastructure, brings together multi-disciplinary expertise, resources and skills from IoT, Machine Learning and Edge Computing to heavy industry and key rail-sector partners.