Social Distancing and Traffic Insights

1. The Opportunity

RBK and LBS officers expressed a strategic requirement to better understand how the Council could support the reopening of the highstreet (and other areas in the borough) while still helping to protect its residents. The need for improved data insights about human and traffic movements, and interactions at a street-level will allow the councils to provide tailored and timely interventions where they are deemed necessary, and in the public’s interest.

The need to find answers to the following questions has underpinned the team’s thinking, and this can be achieved without resource intensive intervention:

  • Is there a way of monitoring people’s movement and proximity to others so that we can use the data to identify areas where social distancing is not happening? 
  • Can we monitor the impact of changes to roads or pavements to gather evidence as to whether the changes were successful or not? 
  • Can we get insights on people’s movement patterns to highlight changes from what was previously normal so that we can predict and better plan for change as it happens in real-time?
  • Can we gather data to understand the busyness of all of our local centres to better optimise service delivery and reduce negative impact to residents and businesses?

Examples of interventions the Council might need to make are as follows: the removal of pedestrian barriers on pavements to provide additional room along walk-ways or crossings; the temporary closing of cycle lanes to make space for pedestrians (in line with the Active Travel Scheme); closing of bus stops at specific road points due to increased queues by shoppers at nearby stores; redirecting foot traffic down specific routes to minimise impact of bottlenecks; and monitoring public areas outside of bars and restaurants to ascertain if overcrowding is taking place.

The option to expand to other SLP boroughs will be explored and progressed if suitable opportunities appear. However, it was determined that Sutton will lead the initial deployment due to shared service opportunities with Kingston (Highways). Key learnings will be used to support the longer term sustainability plan of IoT in local authorities which will be delivered as part of the SLP InnOvaTe Project.

2. How will the Solution be delivered

A pilot to trial the use of 30 “smart video” sensors, is being deployed. Deployment will take 6-12 weeks to implement from order and will run for a period of 12 months to assess and quantify benefits. 

Key goals the project team have factored into the deployment

  • The provision of anonymous,accurate and up-to-date data, needed to support council decision-making for social distancing measures in high footfall areas.
  • The system chosen is based on intelligent video analytics performed by powerful sensors and processors which, when combined with advanced machine learning algorithm processing, provide not only data points related to the measurement of distance between individual pedestrians, but will also deliver a detailed breakdown of traffic flows, journey times and vehicle classes in addition to density of vehicle population in a chosen zone to support wider understanding of movement within the public realm as a whole.

[An example solution showing an example of measurement between pedestrians calculated with pedestrians coming within 2m of each other from stock footage; red shows <2m; yellow 2-3m; and green >3m]

The requirement for a solution to both allow for traffic counting and social distancing monitoring will deliver new outcomes and data sets for the borough which will be of great interest to the service areas and stakeholders concerned.

3. Technical Overview

Hardware

Sensors are being deployed which contain a camera and a processor to facilitate the collection of real time, anonymous data on how the public space is being used by pedestrians and road users. 

Software

Web-based dashboards will be made available for each borough to visualise sensor data for users. This will highlight live, historic and predicted data being generated by the sensors, across a map view showing the locations of each of the sensors and their individual data sets.

Data Considerations

The following key data considerations have been taken into account:

  • The system does not store any personal data 
  • Compliance with GDPR and latest government security guidance is essential.
  • Access to the system is secure and all data is secured at all times. 
  • The sensor must be able to process the video on site without having to send images back to a central system for processing, i.e. sensor data should be sent to the cloud, and the video itself discarded at source (video will be processed on the device itself with any video frames deleted after capture unless the frame is specifically requested for analysis or maintenance reasons).
  • Each sensor is able to produce multiple data outputs, this includes:
    • social distancing data points (counts for distance less than “x” metres)
    • counts of various road users (e.g. pedestrian, cyclist, car, bus, etc) as well as path traveled through the field of view.
    • journey time data for specific types of vehicles
  • ‘Hashing’ of all vehicle number plates where necessary.

The sensor data will be accessible in at least three different ways:

  • online dashboards 
  • reports
  • API (application programming interface)

4. Expected Benefits

Expected Benefits to Local Businesses:

  • Tailored support and interventions from the Council to assist with crowd management and store re-openings within a COVID-19 situation.
  • Reduced delays to interventions will increase economic benefits for local businesses.
  • Increased revenue due to shoppers having a better retail experience.

Expected Benefits to Residents:

  • Reduced infection risk for residents due to better open space management.
  • Improved retail experience due to improved high street management.

Expected Benefits to The Council:

  • Improved decision-making regarding interventions.
  • Increased efficiency of funding utilised for implementation of measures.
  • Ability to make proactive improvements to routing and infrastructure using advanced warnings from the predictive algorithm and historic data patterns.
  • Faster responses to changes with fewer delays – this will reduce the economic effects of congestion on local businesses and residents.
  • Secondary benefits of traffic data used for insights and strategic decision-making.

 

Get involved

Many local authorities have started to implement IoT systems for a number of reasons. Our approach
is to work with our residents and businesses to turn challenges into opportunities for improvement.

If you have some feedback or an idea of how we can improve our services through the use of IoT technology,
we’d love to hear from you. Email Andrew Parsons or Pierre Venter to share your thoughts.

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