NoiseAbility - making sense of noise.
Our vision is to demonstrate that cities can holistically incorporate noise measurement into cities’ management of urban spaces to improve the liveability of our cities.
The NoiseAbility project develops the capacity for cities to understand noise in the context of the citizen’s perceived level of noise acceptability. A report published by the World Health Organisation identified environmental noise as the second largest environmental health risk in Western Europe. Placing the social cost at between £60 billion and £100 billion per annum.
The NoiseAbility project will bring together targeted IoT sensor data with a wider citizen-centric engagement around noise across the pilot cities. We will engage with citizens throughout the pilot using an online tool to track noise acceptability - establishing a relationship between specific user groups and noise types, levels, and duration. By linking noise monitoring data with other city and citizen-centric data via USMART – a data integration & insights platform – we will identify the acceptability of noise to specific citizen ‘personas’. Enabling the development of a powerful predictive tool for noise planning, linked to other strategic city objectives to mitigate noise pollution.
We bring two new cities to the SynchroniCity programme – Bilbao and Edinburgh that have made noise pollution a priority (to be joined by Core City, Eindhoven). These cities are renowned for distinctive compact multi-functional urban form, linked by communal urban spaces and streets that attract high visitor numbers seasonally.
USMART Environment integrates ANY data from ANY source including sensors to monitor air quality, noise pollution and waste monitoring. Our customisable AI modules generate repeatable insights enabling organisations to take the necessary action. Improving our places and advancing sustainability goals that ultimately unlock circular economy benefits.
Automatically digest data and generate predictive diagnostics and insights.
Analyses current conditions to identify deviations from normal operations.
Identify AI opportunities with our Data Discovery workshops.
Real-time sensor integration with problem identification.
Air quality, noise pollution, waste monitoring and other environmental sensors.
Image processing and analytics with label correction and creation..
Dynamic rules and recommendations, anomaly detection and noise filtering.
Detailed analytics and circular economy dashboards for specific organisational areas.
Combines the latest machine learning libraries with our pre-trained AI.
Build a data community of developers and data scientists.