Highways UK 2019 Starts in



6/7 November 2019, NEC, Birmingham




Cost category shortlist

01 TinyMobileRobots

Robot automates premarking, surveying and staking out

What is your proposal?

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.

What does it do?

The robot is used for as-built surveys and marking positions of asphalt and equipment during construction. Easy to set up, it can be used by any personnel with minimum training and experience. The TinyPreMarker takes electronic technical drawings and prints them in the real world. The robot integrates with the top GPS equipment manufacturers and offers precision down to 1 mm when receiving position input from a total station.

How does it meet the challenge?

The TinyPreMarker replaces dangerous, costly and labour-intensive surveying tasks. It is extremely efficient, saving working hours and thereby reducing the costs of road building. The rugged design and light weight (18 kg) make it easy to handle and reliable even in rough conditions. 

Jens Peder Kristensen

jpk@tinymobilerobots.com

https://tinymobilerobots.com/

 

02 Synaptiv

Turning data from connected vehicles into road condition insights

What is your proposal?

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.

What does it do?

The cost of managing road assets can be lowered by using advanced analytics to transform the data generated by connected vehicles into actionable insights around road quality assessment. The system leverages data from vehicles already travelling on roads, instead of employing expensive surveying equipment.

How does it meet the challenge?

The current method for assessing road skid resistance is expensive, disruptive to traffic, with surveys often conducted just annually. Our innovative approach uses wheel speed and accelerometer signals to identify actual vehicle skidding events. Similarly, local authorities and road maintenance contractors employ staff to carry out manual inspections to identify potholes. But by using accelerometer and wheel suspension data, Synaptiv can dramatically lower the cost of identifying potholes, cracks, and determine the overall health of the road surface.

Matt Lewis

m.lewis@synaptiv.ai

www.synaptiv.ai

 

03 Yotta

Smart monitoring of drainage assets identifies network and maintenance priorities

What is your proposal?

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.

What does it do?

The gully sensors will link to the back office where officers can make instant decisions to pro-actively address and prevent flooding instances on the network. This data will then be utilised for long term planning, whole life costing and maintenance activities which will eventually be linked to carriageway condition data.

How does it meet the challenge?

Drainage is a major issue for highway authorities causing issues around flooding, property and highway, but also causing significant damage to other highway assets. Our solution uses intelligent infrastructure to pro-actively manage instances of flooding and to collect data that can be used for long term maintenance decisions. Previous case studies of gully sensors have shown there is a potential to reduce the cost of gully cleaning by up to 20%. Not only are we looking to save costs on cleansing but also reduce the cost of damages caused by flooding, thereby reducing the whole life cost of drainage and carriageway assets.

Emily See

contactus@weareyotta.com

www.weareyotta.com

 

04 OXEMS

Artificial intelligence set to transform underground asset monitoring system

What is your proposal?

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.

What does it do?

The system enables fast and pinpoint accurate location and identification of buried assets so contractors operating in the street can undertake work quickly, with minimal footprint and impact on the surrounding area. Development of a new layered data model using machine learning techniques with quantum technology gravity sensors augmented with InSAR (a radar technique used in geodesy and remote sensing) and drone captured data will enable continuous monitoring of road infrastructure.

How does it meet the challenge?

Deploying the current system minimises the scale and duration of roadworks reducing congestion, associated air pollution, and costs. The new layered data model potentially offers continuous monitoring of road infrastructure, which could, for instance, identify early structural movement, reducing maintenance work, costs and disruption. Ultimately this means greater use and efficiency of existing and new road assets, and lower whole life operating costs of the road network.

Kevin Gooding

kevin.gooding@oxems.com

www.oxems.com

 

05 Barter For Things 

Internet of things and machine learning technology make gritting decisions

What is your proposal?

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".

What does it do?

The technology provides a step-change in cost of road-surface data. Tens-of-thousands of low-cost, in-road sensors send real-time temperature, salinity and moisture data to decision makers. 

How does it meet the challenge?

The challenge is met by virtue of a Department for Transport "Connected Vehicles" project that leverages new UK infrastructure specially designed for low-cost, long-battery life devices. The innovation is taking a real-world problem and applying relevant, emerging technology. 

Alex Barter

alex@barterforthings.co.uk

www.barter4things.com

 

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