MultiSens²e aims to develop a Multi-Sensor Farm Monitoring ecosystem, which is capable of predicting plant diseases earlier than the signs of disease are noticeable with human senses by detecting plant stress using various sensors and software solutions, such as artificial intelligence and machine learning. Another ambition of Multi-Sensor Farm Monitoring system is to contribute optimal resource-utilization e.g. irrigation, fertilization. These solutions lead not only reducing the costs and necessary resources such as water and chemical pesticides, but also minimising pressure on the environment.
A Multi-Sensor Farm Monitoring system includes the following key solutions based on preliminary concepts:
Various range of sensors. Multi-sensor means that the system consists different type of sensors (e.g. several types of cameras, such as thermal and hyperspectral cameras, weather sensors, odour sensors, soil moisture sensor), with different placement (e.g. fix-placed IoT sensors, satellite/drone imagery, mobile phone sensors) for multi-scale purposes: from micro scale (single leaf or plant) to macro scale (entire parcel observation).
Software solutions for processing data. Processing sensor data innovative software technologies, preferably developed under Horizon 2020 program, have to be used as data mining, machine learning algorithms, artificial intelligence. In case of on-field sensors noise correction is a priority.
Software solutions for evaluating and utilizing data. The most common problem based on Bank of Challenges survey is that even when the data from sensors is available for farmers, there is a shortage on data explanation solutions, especially when different types of data come into picture. This problem need to be addressed.
Networking. To increase the benefits of digital technologies of small- and medium-sized farms networking is essential. Sharing knowledge, expertise and even data between farmers is one of the key element in avoiding digital divide between small and large farms.
Get in touch with us!