Watering optimisation

ENVIRONMENT – WATERING OPTIMISATION

How can we use data to optimize and automate the watering of (public) green spaces in order to realise water and labour savings?

 

Challenge Identifier: BC5 – 2018 – SQ
Sponsor City: Saint-Quentin
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Description

The digital roadmap of Saint-Quentin retains as a top priority the development of sustainable cities by acting on two levers: optimization of energy consumption and improvement of the (internal) efficiency of public service. Saint-Quentin has a focus on encouraging the development of autonomous solutions in public services.

In this framework, the city wants to deploy an intelligent system in green spaces that can control watering in order to optimize water consumption and make the system totally autonomous. The main difficulties lie in the ability to develop an autonomous solution to control the triggering and stopping of watering heads and to produce this solution at a reasonable cost for a middle-sized city.

In particular, the lack of data on the prevailing conditions in green spaces limits the capability of the city to optimize water consumption and realize energy savings. Currently, the only data used to monitor watering heads is a day-night cycle.  Further, municipal staff have an increased workload since the introduction of a new national legislation that forbids the use of chemical products to manage green spaces. Therefore, this is also question of internal efficiency in order to limit the time of the city’s staff on the field with the support of a full autonomous system.

Saint Quentin has already explored some existing solutions on the market, but they are not aimed at the medium-sized city market.

Expected Outcomes

  • Optimise water consumption in green spaces by using or / and combining different parameters: weather data and forecast; water needs in function of green space’s profile / typology;
  • Monitoring tools for city staff such as a dashboard that gives an overview of historical and present conditions of green spaces;
  • Solutions linked with local weather stations;
  • Remote and autonomous controls for watering systems.

Expected Impacts

  • Energy savings by optimizing water consumption
  • Reduction in water and labour costs
  • Replicability, interoperability and transferability of the solution

Datasets

  • Events calendar related to occupation of public green spaces;
  • Location of green spaces;
  • Weather datasets from weather station owned by of the local government or from collaborative weather network if needed to gather forecast weather;
  • Prevailing environmental conditions of public green spaces through sensors (air humidity; ground humidity)
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