Smart data for safer cycling

As part of Manchester’s CityVerve two-year smart data/Internet of Things demonstrator project, data collected from smart cycle lights is intended to improve road safety.

180 volunteer cyclists with smart sensors are currently generating data to help to direct future road safety measures in Manchester. Smart cycle lights from Northern Ireland-based See.Sense are linked to a smartphone app via Bluetooth and transmit data to a central data hub.

The project is part of the Manchester’s wider two-year CityVerve programme, which kicked off in July 2016 and runs to June 2018. Across Transport and Travel, Energy and the Environment, Health and Social Care, and Culture and the Public Realm, CityVerve seeks to draw together data from multiple sources to improve the city. It is led by Manchester City Council and involves 21 organisations, including local universities, NHS trusts, start-ups and global technology companies.

Using Data for Safer Cycling

The first See.Sense intelligent light was launched on Kickstarter in October 2013, with the current ICON offering following in 2016. There are front and rear lights, available on-line (https://seesense.cc/) and now increasingly through outlets around the world. The company was one of the winners of BT’s Lab Connected Cities competition and it was BT’s involvement in the transport hub within CityVerve that brought the company into the fold.

Volunteers were sought for the cycling project and these were given a heavily discounted price on the ICON lights. The trial started on 14th August and runs until the end of the CityVerve project. The anonymous and aggregated data is being collected and will be available along the lines of the overall project.

As with anything like this, there is the question of bias. After all, a prerequisite is an Android smart phone, which immediately excludes many people. The aim, says Professor John Davies, lead researcher at BT, has been to reflect the age and gender of the city within the selected trialists. This was helped by the fact that the scheme was heavily over-subscribed, he says.

The motion sensors can detect road conditions and bike movement. The lights flash brighter and faster in high-risk situations. At the simplest level, cyclists’ journeys can be overlaid onto route maps to show where they are travelling. Secondly, data on speed, braking and wait times can be added to show where there’s congestion, near-misses or accidents. The data also provides insights into road conditions as the sensors collect data on ride smoothness.

This data could be used to help Manchester City Council make better investment decisions about the city’s cycling infrastructure including upgrading the busiest routes, focusing on improving safety at hotspots, and prioritising road repairs, including filling in potholes.

These are relatively early days for the trial, says Professor Davies, but useful information is already being generated. See.Sense’s current commercially available ICON lights do not include data collection but this technology, developed alongside data scientists from Queens University, Belfast, is also being tested in trials in Belfast and Dublin.

The Wider CityVerve Project

The open innovation part of the overall CityVerve project will start in January, when the partners and third-parties will start to develop apps based on the open data. A series of business challenges will be defined, around the four areas of focus, at which point “we’ll start to test our technology and the value of the data”, says Professor Davies.

The CityVerve Data Hub is linked to around 200 sources, including parking data, automatic traffic counts, Met Office weather observations, air quality data, live public transport data, and Highways England traffic density data.

An Asset Mapping/smart building management stream is intended to connect energy, water and gas meters as well as harnessing low-cost sensors to measure things like CO2 levels, occupancy and movement inside buildings.

Cisco, with Ordnance Survey, is compiling what Professor Davies describes as “a very fine-grained 3D map” of Manchester’s streets. Knowing the height of street furniture will be important, he points out, for drone deliveries, for instance.

The project uses the Hypercat specification to create interoperable, machine-readable catalogues and APIs for the IoT data. Some IoT devices are connected via a Low Power Wide Area Network, powered by six servers, designed specifically to support wireless, lower power IoT sensors. Other connectivity options include wifi and SIM-based mobile data.

Also part of the project is a privacy portal that allows Manchester’s citizens to decide how their personal data is collected and used within the project. It uses oneM2M’s Privacy Policy Manager (PPM) specification and is integrated with the CityVerve Data Hub.

CityVerve is underpinned by a £15 million collaborative R&D budget (including £10 million from the UK government) and follows on from a smaller scale government-led pilot within Milton Keynes.

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Source: Transport for Greater Manchester

By | 2017-12-18T17:09:41+00:00 Dec 18th, 2017|Transport|0 Comments

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