IoT applied to Vineyards
Since 2005, researchers at the Universidad de Castilla La Mancha have been involved on the design and development of distributed computer-based solutions for agriculture. Early activities focused on the introduction of wireless sensor networks into an important sector in Castilla La Mancha: vine growing. The main goals of the activities comprised the development and deployment of full operational wireless sensor networks for the data capture, processing and visualization of environmental parameters: temperature, soil and air humidity among others.
Current efforts are focusing on the use of IoT technologies enabling the gathering, communication, processing and visualization of the data being captured by a network of sensors deployed in vineyards. The main challenges and research objectives are two fold:
- AGRONOMICAL ISSUES. The main aim of the research efforts is to develop tools offering valuable information to grape growers and wine producers. The data collected by the sensors jointly with other sources of information should prove invaluable to all stakeholders. The activation of irrigation systems and pesticide sprayers can be timely and wisely planned based on the information extracted from the data gathered by the sensors. The selection of the best grapes will be based on the information extracted from the data automatically collected throughout the season. Furthermore, the integration latest developments on IoT technologies including Cloud services and intelligent machine principles should allow for the automatic book-keeping recording of operational parameters and key agricultural performance indices.
- TECHNICAL CHALLENGES. Computer and communication specialists should gain invaluable experience on the design and development of a fully integrated system making use of a state-of-the art technology. The deployment of wireless networks and computer-based systems in the fields requires cost-effective and reliable solutions addressing issues, such as, the management of power to be supplied to the sensor nodes, reliability and resilience of networks exposed to power outage and interferences, security and privacy of proprietary data.