Urban Data Talks #1
We are navigating unprecedent times – our economy and local communities are under attack by a virus that has wreaked havoc and thrown the world into a global crisis. In these times of uncertainty, the availability of good data is more important than ever before; in order to help us make the right decisions to prioritise how to best help the most vulnerable in our community and to increase our confidence to take the right steps to emerge to a much changed but hopefully better post pandemic world.
Our first urban data talks event focused on confidence - how urban data can enhance the confidence of members in our communities through empowerment, but also how confident can we be in the behavioural models that we build based on urban data.
We had the pleasure to learn about two recent case studies of real time urban data use.
The first one was presented by Mark Stanley from Thingitude and focused on improving public street safety for women. Mark developed MyWay, an app for women students in Reading which leverages real time light and noise from a recent IoT deployment in the town centre, bus information and crowd sourced data to help its users decide on the best route at night – all while being connected with other users to provide additional comfort and safety. After a successful pilot with 82 students, the app will go live later this year for the entire university population with more launches envisioned in other towns and universities.
The second case study, InDependAbility, shared with us by Rory Maxwell from Ethos VO, looked at how urban data can empower people with disabilities to grow more confidence in their use of public transport and prevent them end up in social isolation. Working together with Adult Social Services of Bracknell Forest Council and local bus operator, Rory installed real time bus occupancy trackers to establish real time seating availability for users who really depend on it. This information together with live bus timetables was fed to in-home displays at people’s homes, GP surgeries, and other public sites. Based on this information elderly and vulnerable citizen now have the opportunity to make the right choice of transport and better plan their journeys around town by avoiding busy services. A more fine-grained understanding of occupancy patterns allows transport providers to better plan and revise routes based on real demand. Local authorities can make better decisions on how subsidies are utilised.
Both case studies demonstrated examples of how appropriate use of urban data can boost the confidence of citizens to move around their city and increase their safety by avoiding their exposure to potentially harmful situations. They all involved an element of real time data collected by IoT infrastructures deployed in an urban environment and end user services that leverage this data to provide the aforementioned benefits through better decision making. What I liked about these examples is that they are applicable to many other cities and towns and could be easily replicated by other local authorities.
In her talk, Claire Fram took us through some of her work at ARUP’s city modelling lab, where she uses agent-based models to resemble behaviour in cities. Her models utilise a number of data sources ranging from physical city and service infrastructure to citizen activity. One of her challenges is it to create a good enough model that her clients care about and provide enough proofs of confidence that her model is reflective enough for the modelling scenarios. An interesting insight that emerged from the current conversation was the reliance of modelling populations based on census 3data. Typically, such data is only collected about every 10 years, so the representative nature of this data diminishes year after year. The most recent census has been completed only last month. While most up-to-date will be soon available, it is unclear how reflective this data will be in the long run due to the behavioural bias caused by the recent pandemic. There might be a need to run another census in the near future to get a more reliable data set to work with in the years to come.
The evening left us with plenty of food for thought – we walked away with more confidence that urban data can indeed provide a useful enabler to help improve the resilience of our cities and the quality of life of our communities. I am already looking forward to the next event later this month.