Highways UK 2020 Starts in



4/5 November 2020, NEC, Birmingham




PA Consulting Dome

Costain Intelligent Infrastructure Challenge

Costain Intelligent Infrastructure Challenge

Many thanks to everyone who made the third Intelligent Infrastructure Challenge (IIC) at Highways UK 2018 such a success. Especially thanks to our finalists, the IIC sponsor Costain, our many judges, the IIC steering committee and of course our visitors. Congratulations to the four category winners, and the overall winner, Tangent Energy.

The winners, finalists and judges for the four categories are:-

Safety category

Winner: See.Sense

Finalists: Xonix, Crypta Labs, Wearable Technologies, Carnell Support Services

Judges: Iain Rillie (Highways England), Tony Scutt (Costain), Raphael Ani (Wayra)

Cost category

Winner: OXEMS

Finalists: TinyMobileRobots, Synaptiv, Yotta, Barter for Things

Judges: Simon Yarwood (Knowledge Transfer Network), Darren Capes (Department for Transport), Rukshan Soysa (UK Intelligent Transport Systems Society)

Pollution category

Winner: Tangent Energy Systems

Finalists: Church Hill Solutions, Pure Air Industries, Atmo Tech, Off Grid Energy

Judges: Anthony Ferguson (Department for Transport), Steve Clark (British Parking Association), Alice McLean (Temple Group)

Congestion category

Winner: TransPix

Finalists: Atkins, Neural Mind, Cleverciti Systems, 1.21GigaWatts

Judges: Paul Doney (Highways England), Alex Weedon (Transport Systems Catapult), Adrian Ulisse (INRIX)

You can access the finalists' presentations using the links below

 

Safety category shortlist

01 Xonix

Camera based monitoring system with built-in artificial intelligence

The Xonix vision system (xVS) is a completely modular and scalable, small, lightweight camera and sensor system with built-in artificial intelligence. It can be used in a fixed position, in a vehicle or on a drone. The xVS can perform video analytics, automatic number plate recognition, classification, detection, tracking, facial recognition and monitoring. The built-in artificial intelligence can process images and sensor data autonomously in real-time to provide the exact data output that is required.

 

02 See.Sense (category winner)

Bike lights that monitor road surface quality

See.Sense creates award-winning bike lights which give cyclists more visibility on their ride, and cities more information on their roads. Technology inside the lights detects road surface quality and insights are shared with cities to improve safety, reduce congestion and pollution. See.Sense bike lights monitoring data can be used to predict degradation or pothole formation, for cost-effective repairs. The information gathered on cyclist journey and experiences also helps to efficiently design for safer cycling infrastructure, which helps address barriers to cycling.

03 Crypta Labs

Making CAV communication secure from cyber attack

Cyber security vulnerabilities could slow the adoption of connected and autonomous vehicles (CAVs) due to consumer safety concerns. Crypta Labs' proposal is to embed its quantum seeded encryption technology to provide an all-encompassing system to secure CAV communication.

 

04 Wearable Technologies Ltd (WTL)

Clothing that monitors and helps reduce highway workers' exposure to risk

WTL embeds washable electronic networks into industrial PPE jackets and vests, enabling sensor information from a wide choice of devices to be aggregated onto one central control dashboard for real-time alerts and collation of long-term occupational health data. In so doing it enables earlier decision making and better identification of issues to reduce highway workers' exposure to risk.

05 Carnell

Overhead hazard alert system

OverheadSafe provides a clear and visible alert to the presence of an overhead hazard. The smart PPE vest with integrated LEDs continuously flashes whilst in the proximity of a blue cone. The cone is connected to our back-office solution, passing various data items related to activities and risks monitored on site. OverheadSafe uses GSM connectivity along with GPS, accelerometer and gyroscope sensors, with the data uploaded to the cloud. Using AI, we will provide invaluable insights into people's working behaviour which will inform better working processes and procedures.

 

Cost category shortlist

01 TinyMobileRobots

Robot automates premarking, surveying and staking out

The TinyPreMarker is a light-weight, high-precision global navigation satellite system robot for premarking, surveying and staking out. The robot saves time, reduces pollution and cuts overall road construction costs. It removes the need for operatives to work in or beside live carriageways and allows advanced and complicated surveying tasks to be completed with an extremely user-friendly tablet interface.

02 Synaptiv

Turning data from connected vehicles into road condition insights

Cars are packed with hundreds of sensors that provide information about the vehicle, such as its speed, location, wheel suspension height and the status of the wipers. Synaptiv has identified an opportunity to use advanced analytics to transform this data into actionable insights to assess road skid resistance and pothole detection.

03 Yotta

Smart monitoring of drainage assets identifies network and maintenance priorities

Dorset and Yotta's proposal utilises internet of things data and smart technologies to gather greater information on Dorset's drainage assets. This will deliver real-time data across the network, providing information on the assets use, condition and demand giving the ability to make long-term strategic decisions on maintenance.

04 OXEMS (category winner)

Artificial intelligence set to transform underground asset monitoring system

The OXEMS underground asset monitoring and management system consists of markers buried with utility assets at key points such as joints, valves, bends - all points that may need to be located quickly and efficiently in the future. The system underpins the development of a new artificial intelligence-based model that could offer a cost-effective approach to managing and monitoring road infrastructure continuously.

05 Barter For Things 

Internet of things and machine learning technology make gritting decisions

We propose to cut the UK's gritting costs by 10% in the next five years. We plan to use emerging internet of things and machine learning technology to support the human decision of whether "to grit, or not to grit".

 

Pollution category shortlist

01 Church Hill Solutions

AI system that detects littering from vehicles and supports enforcement

LitterCam is a camera-based artificial intelligence platform designed to detect both littering from vehicles and unsecured load offences. It automatically transmits suspected offence footage for human validation and then requests driver details from the DVLA for enforcement and education purposes.

02 Pure Air Industries

Technology to actively clean air outdoors

 Our basic premise is that instead of managing pollution, why not clean it. Exhaust fumes are hotter than the surrounding air and rise. Patent-pending units and technology capture and clean the air from particulate matter and NOx, O3, CO2, CO, etc. and they are conveniently placed on light posts just by the road. This means we are able to grab pollutants close to the source and before they get diluted further.

 

03 Tangent Energy Systems  (category winner and overall winner)

Reducing the use of on-site diesel generators

Tangent Energy's site energy storage systems automatically manages available power sources such as diesel generators, PV, wind, or the grid and stores the electricity in a battery which it dispatches in a controllable manner. The result is a typical site generator is switched off for over 60% of the week. The system also provides air pollution monitoring to report on CO2, NOx, PM, fuel and energy consumption. The system powers the site from its batteries. When the batteries are low the system automatically runs the diesel generator to recharge itself. The loads are prioritized and selectively switched on and off to achieve the most efficient load profile. All the data is visible in the web platform.

04 Off Grid Energy

Reducing the use of on-site diesel generators

Thousands of diesel generators run 24/7 in the construction, maintenance and operation of our highways, that create noise, pollution and cost money to run. gridtogo is a ruggedised, smart energy storage solution, suitable for a range of applications that include being a hybrid power generation system for construction, or a means to support limited grid power supply for EV charging. It achieves substantial cost savings while also having significant positive environmental impact. gridtogo controls a diesel generator, turning it on and off, and making it work most efficiently. It uses energy stored in the battery for clean, consistent power supply. It can also be used to boost the capacity of a limited grid connection, eliminating the need for a generator altogether.  

05 Atmo Technology

Benchmarking and analytics tool for on-site air quality and noise pollution sources

Atmo Technology enables data-driven decision making by tracking the changes in a site's environment over time as well as the effect control measures are having. Our portal and software allow for benchmarking and data analytics for different areas and different times. In addition to tracking air/noise performance over time, our sensors can give values of personal exposure to workers who may be present in the area, ie during construction and maintenance of roads and buildings 

 

Congestion category shortlist

01 Atkins

Redeploying the SVD radar network to monitor traffic density and congestion 

The project proposes using existing selectable vehicle detection (SVD) radar sites installed on the all lane running J23-27 section of the M25 and reconfiguring them for monitoring traffic density and congestion. The proposal is to demonstrate that SVD radars are suitable for existing Motorway Incident Detection and Automatic Signalling (MIDAS) requirements. The SVD radars provide near 100% road coverage and, if configured for this purpose, could potentially replace the existing MIDAS sensors, improving safety and significantly reducing the infrastructure costs of implementing future smart motorway schemes.

02 Neural Mind

Artificial intelligence powered camera system offers analysis based on actual vehicle data

Neural Mind is an artificial intelligence powered camera system combined with a cloud based big data analytics platform. The system empowers road operators to make informed decisions based on true individual vehicle metrics and unique classifications such as 'electric vehicle', enabling the easy implementation of clean air zones or planning electric vehicle charging locations exactly where they are required.

  

03 Cleverciti Systems GmbH

Informed parking decisions based on real time data

Around 30% of traffic and subsequent pollution is caused by drivers looking for parking. Studies show that real time detection of available on-street parking spaces can decrease traffic, pollution, time and distance to park by 30% or more. Cleverciti sensors monitor the availability of parking spaces in real time. This data is then integrated into existing apps, unique bespoke apps, navigation devices, parking guidance systems, variable message screens, parking management or smart city platforms.

04 1.21GigaWatts

Applying the concept of an air traffic control system to the road network

The Responsive Traffic Controller (RTC) is a unique situational awareness module to be embedded in the road infrastructure that enables the traffic control system to intelligently understand what is happening on the road, preform centralized scene analysis and actively guide vehicles, like the air traffic control system guides planes.

05 TransPix  (category winner)

Use of actual traffic patterns improves effectiveness of traffic management systems

SmartFlo offers intelligent data analysis in real-time for optimizing real-time urban transport congestion management. Videos are collected from internet of things cameras, processed in real-time in-situ or the cloud. The system is able to detect variables including turning-movement, lane occupancy, queue length, vehicle classification, lane-merging, lane-changes, congestion, accident, road-works, stopped vehicles, and traffic patterns such as the interaction of freight in port cities.

 

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