Garden Monitor is a mobile application developed in the context of the MK:Smart project. This project is developing innovative solutions to tackle key sustainability issues and support economic growth in Milton Keynes.
An important issue for the project concerns the sustainable management of water resources. Milton Keynes, being located in one of the driest parts of the country, is under pressure. With a rapidly increasing population and in the context of climate change, new solutions are needed to reduce water consumption, if this growth is to be sustainable.
Every year, a large amount of water is wasted through inefficient watering of domestic gardens. To help reduce water wastage related to gardening activities, we have developed Garden Monitor, a mobile application which supports efficient water management in gardens. Garden Monitor forecasts the conditions of a garden over the following ten days and generates a customized calendar advising users on whether and when they may need to water their garden. It also produces a historical record of a garden in terms of soil moisture, temperature, rainfall and so on, allowing users to monitor the status of their garden and to understand how it reacts to variations in weather conditions.
From July to October 2016, we have conducted an evaluation of Garden Monitor with eight users in Milton Keynes. This evaluation was designed to assess the performance of the machine learning of Garden Monitor, as well as its value to users and its usability. At the end of the evaluation, we asked our users [...]
We are currently starting an evaluation of Garden Monitor in Milton Keynes in order to assess the performance of its learning engine, value to users, and usability. To this end we are looking for early testers keen to try this new technology in their garden. If you are interested in the evaluation, please contact [...]
How it works
- The Koubachi Plant Pro 2 sensors are used to measure soil moisture and meteorological data, which are then stored in the Data Hub.
- The Dark Sky API provides weather forecast data.
The Garden Monitor API is at the heart of the system. It is this API that carries out the machine learning processes in order to forecast future soil moisture values. The algorithm performs a multiple linear regression on seven parameters: soil moisture, max temperature, min temperature, pressure, humidity, rainfall, and wind speed. With the resulting models of gardens, the predictions for future soil moisture values are then computed using the current day’s soil moisture value and weather forecast data. Finally, the Garden Monitor Android application reads the data computed by the Garden Monitor API and displays it to the user.
Angelo Antonio Salatino
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