Parking technology Predicting the future Qucit won the judges award on this years Innovation Trail at Parkex for its parking software that helps direct parking enforcement to where it is needed most. Account manager Alix Paricard explains how this works on the ground, using a case study from Paris Q ucits goal is to improve the quality of city life. We do this by building digital models of cities using data from our clients and applying predictive machine-learning algorithms to help them plan their work more effectively, for the benefit of all. We build digital models of cities using data from our clients and apply predictive machinelearning algorithms to help them plan their work more effectively Since January, we have been working with parking management company Moovia. It has been in charge of parking enforcement in the boroughs of northern Paris for the past 20 months, covering approximately 43,000 parking spaces. Moovia uses tools provided by Egis Parking for its enforcement operations. Egis Parking asked Qucit to tailor its ParkPredict Control platform to help plan and supervise enforcement officers routes, and Qucit worked with Moovia to roll this out. The planning algorithm integrates payment-rate predictions in each zone so officers can be directed to areas where enforcement is needed and improve on-street parking compliance. Business benefits Before ParkPredict Control was deployed, routes were planned by Moovia on the basis of an average payment and occupancy rate recorded over the previous 15 days of activity, the objective being to prioritise the areas that needed to be visited. However, it did not take into account certain parameters, such as school holidays or weather conditions, says Ccile Mohamed, operations manager at Moovia. It was based every day on time-consuming, manual processing of databases. As a result, there was a serious lack of information needed to produce accurate forecasts for violations. With ParkPredict Control accessible in the office and on the move, Mohamed says the platform is very easy to use and an important tool for decision-making. We save time because predictions are accessible in one click. This allows us to spend more time developing our enforcement strategy. In short, our rounds are better planned The predictions give us real insights into user behaviours over the next few days, which we then corroborate in the field. We are able to anticipate more reliably where motorists will park and to what extent they will pay their parking fees. Finally, it is a real decision-support tool: we save time because predictions are accessible in one click, and ratios are automatically calculated and visible on a heat map. This allows us to spend more time developing our enforcement strategy. In short, our rounds are better planned. Positive feedback The close working relationship between Qucit and Moovia during the implementation of ParkPredict Control enabled feedback to be taken into account when developing the tool and adapting it for Moovias business needs. Now that we use it daily, the relationship with Qucit continues, says Mohamed. We contact them with any queries and get a feedback within the day. britishparking.co.uk 31 10:34 PN Sep19 pp30-31 QUCIT v2 PL.indd 31 22/08/2019 11:57