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3D Precision Farming using Internet of Things and Unmanned Aerial Vehicles in Greenhouses

The general objective of this project is the adaptation of existing technologies used in a precision agriculture (PA), into an indoor (greenhouse) prototype system which includes the use of both an unmanned ground and aerial vehicles (UGV and UAV). The term precision agriculture refers to the use of information technologies (IT) to help farmers manage the optimal growth of their crops thus ensuring profitability and sustainability. Furthermore, PA has also been known to help the environment by avoiding unnecessary spaying of pesticides as well as excessive use of water and fertilisers. The use of unmanned systems offers higher spatial resolution data compared to satellites. The real-time data of interest to the farmers and management tools/software includes soil properties such as moisture, compaction, salinity and nutrients (nitrogen (N), phosphorus (P) and potassium (K)), and crop monitoring which includes vegetation indexes such as Chlorophyll, Leaf Water, Ground Cover, Leaf Area, Normalised Difference Vegetation Index (NDVI), etc. UAVs have been used in PA for bird eye view, for insect identification using cameras and Lidars, and even actuators for autonomous spraying of pesticides, whereas the use of UGVs provides bottom-up capabilities identifying insects hiding under the leaves and for crop planting and harvesting. The innovation of this project is the UGV and UAV for indoor (greenhouse) PA applications where GPS signals are very weak or non-existent. In addition, this work will validate high-precision cm-level, 3D positioning techniques required for unmanned vehicle indoor localisation and navigation

Funding Body: Cyprus Research and Innovation Foundation

Project ID: CONCEPT/0722/00100

Duration:: 1st April 2023 - 31st December 2023 (9 months)

Funding Received: 39.902,56 Euros

Host Organization: Center of Interdisciplinary Science Promotion and Innovative Research Exploration (InSPIRE)

Coordinator: - Dr Stelios Ioannou

Researchers: - Dr Marios Raspopoulos , Mr Andrey Sesyuk, Mr Demetris Kallasides

News

(31 December 2024)

Project Ends

(1st April 2023)

Project Starts

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Deliverables

Publications

-J. Ye, S. Ioannou, P. Nikolaou and M. Raspopoulos, “CNN based Real-time Forest Fire Detection System for Low-power Embedded Devices,” 2023 31st Mediterranean Conference on Control and Automation (MED), Limassol, Cyprus, 2023, pp. 137-143, doi: 10.1109/MED59994.2023.10185692.