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How can AI and smart tech tools improve local places through optimising the delivery of services?
What is the challenge?
Delivering council services such as traffic management, incident management and waste or recycling services are vital to making sure that resident’s public environments are clean and safe. Many of these services need to be consistently delivered on a daily or weekly basis, which increases the requirement for these services to be targeted where they are most needed.
AI and Smart Tech’s ability to provide data based insights on the where and how services can be prioritised can help the council make better decisions enabling efficient resource allocation, and thereby ensuring that services are being delivered where they can have their greatest impact.
Who has designed the challenge?
Why does this challenge matter?
Systematic maintenance and management of streets, roads and other aspects of residents local places is essential for resident's quality of life. Using AI and Smart Tech to gather data that can help assess demand and direct services or automate systems that manage such services, which can lead to an overall increase in resident wellbeing, health and safety as well as overall experience of local places by both businesses and residents.
Meanwhile, AI and smart tech’s ability to synthesise, analyse and leverage real-time data to understand and predict patterns may deliver wider benefits, including helping to reduce carbon emissions and enhance equity in the delivery of services by being data-led.
Moreover, councils desire to achieve efficiency savings and lowering of the cost-of-services means that if the allocation of resources can be better aimed at tasks that will have the highest impact, it may allow for greater overall efficiency of council resources.
What are the considerations and constraints?
Data used from photographic and video sources is especially high risk for data protection and security.
Solution should be explainable and help progress the need for information to be publicly shared for transparency and supporting public change management.
Vendors should support councils on data ownership, interoperability and data sharing which are pertinent to this challenge especially if being integrated with legacy systems.
Seasonality needs to be considered since solutions are embedded in public spaces and open to seasonal changes.
Who are the end users?
Council officers: Using tools to help allocate resources where they are most needed will enhance the ability of teams planning how to deliver services.
Council service delivery teams (cleaning teams, transport operators, emergency services): Smarter resource allocation may help simplify tasks and drive greater efficiency while simultaneously being deployed more effectively to complex tasks.
Local communities: Solution to this challenge will cause improvements in community, resident and business experience.
How is it being tackled now?
Collaborated with technical partners to conduct research detailing problems associated with incident management, bus transport and air quality.
Selected councils have created interactive web tools that can be used for helping direct services for internal and external end users, who have found the tool accessible and easy to use.
Some use of cameras and grading of images to assess litter in different areas across the council. A few councils are exploring the digital twin technology for decarbonisation efforts.
Other councils have been reliant on manual surveying and patrolling methods, which currently utilises a significant amount of council time and resources.
In other cases, resource allocation plans for maintaining public spaces have been seldom updated despite new buildings due to the manual processes required.
There are some examples of tools being used internationally for the managing traffic systems to enable emergency services arriving at incidents quicker.
More specific challenges to consider
How can AI and smart technology:
- be used for traffic and incident prediction and management
- support better routing of public transport through traffic management, with focus on special groups such as school buses
- be applied to reduce congestion on roads
- predict the need for resource allocation based on either historical trends or future inputs (e.g., weather)
- optimise litter management services based on historical or future-oriented input
- be used to improve public places, particularly in terms of waste/litter present , thereby optimising scheduling for litter management
- be used to improve recycling rates.
Start-ups that pitched for the improving local places challenge statement
Alchera uses AI to empower local authorities to investigate historical & real-time bus activity to monitor, evaluate and improve bus networks. Alchera Bus’s data granularity can go down to 20 metre segments of road, minute-by-minute and hour-by-hour reporting, all supported by real-world real-time data gathered from BODS and other data sources. Surfaced insights quantify the economic cost of pinch points to prioritise investment & build business cases alongside desired outcomes like reduced variability in journey time, increased average speed on routes, thereby resulting faster bus journeys. Additionally, Alchera’s route optimisation promotes positive changes such as increased patronage and reduction in associated carbon emissions.
Immense Simulations provides AI tools to public sector officers and their supply chain partners fleet and traffic management tools to enable rapid and consistent assessment of interventions that may affect operations and performance. Their tools provide standardised reports including the locations and times of potential queues, delays and disruption to key routes, likely detour behaviours and associated emissions of CO2 and NOx.
Podaris’s web-based platform leverages cloud collaboration technology to optimise transport planning, analysis, and stakeholder engagement. Their platform enables users to create and analyse multi-modal transport networks — including traditional modes like rail and bus, as well as innovative modes such as micro mobility and personal rapid transit.
The LGA maintains vendor neutrality. This initiative aims to assist the sector with the responsible and secure implementation of AI and smart technology solutions. Vendors presented were assessed and pre-selected ahead of the event. This event does not guarantee business for vendors or providers, nor are councils obligated to procure any presented solutions. Councils may, however, choose to commission a solution through proper procurement channels following the Showcase.