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Stresscan - physiological and interactive monitoring of plants

Grant number: 17/15204-1
Support Opportunities:Research Grants - Innovative Research in Small Business - PIPE
Duration: June 01, 2018 - February 28, 2019
Field of knowledge:Agronomical Sciences - Agronomy - Agricultural Meteorology
Principal Investigator:Gustavo Francisco Rosalin Saraiva
Grantee:Gustavo Francisco Rosalin Saraiva
Host Company:Stresscan Agrobusiness Intelligence Ltda
CNAE: Atividades de apoio à agricultura
City: Presidente Prudente
Associated researchers: Regina da Silva Andrade Saraiva
Associated scholarship(s):18/14632-2 - Stresscan: physiological and interactive monitoring of plants, BP.TT
18/13970-1 - Stresscan: physiological and interactive monitoring of plants, BP.PIPE


Agriculture is experiencing an increase in technologies associated with the production chain. However, the application of current technologies does not overcome one of the great problems of agriculture, which is the waste, or misuse, of resources. In all links of the productive chain there are great losses, one of them being the immense volume of water used inadequately in irrigation systems. Within this context, technologies that aim at better efficiency in the use of resources play a fundamental role, since the demand for resources will be increasing. The objective of this project is to create an interactive system of physiological monitoring of plants, which will enable greater approximation and control of the user with his plantation. A sensor station will be developed that will communicate with the user through an application. In the application will be used two approaches to access information: digital platform and chatbot. The platform gathers all collected data and presents them in the form of graphs and reports, aiming at a more technical approach to the tool. The chatbot will allow the user to interact with the sensor station, receiving alerts and information about the climate and physiological status of the plant. This technology will allow a user-friendly interaction with your plant, where the plant can inform its physiological state and its needs regarding irrigation, sending warnings and alerts to the user. Data will be collected on temperature and humidity of air and soil and leaf temperature of plants. According to research, leaf temperature is a reliable indicator of stress in plants, so it will be used as a physiological reference of the plant. O is based on the IoT (Internet of Things) concept of Internet of Things, offering real-time information on the conditions and needs of plantations to be used in decision-making regarding irrigation and other needs of the producer. The prototype of the sensor station will be developed using measurement technology based on the Atmega® system and a processing system coupled to a computer system. The data transmission from the station will be via Wi-Fi wireless network and the power supply of the station will be made by a solar photovoltaic plate. As a result, the physiological and climatic monitoring station is expected to be developed at an affordable and fair price, using components and sensors of high precision and the best cost-benefit ratio. In this way it will be possible to provide the user with a more adequate monitoring of his plants. The technologies used to build the application will enable the system to acquire an intelligence standard. The data collected by the sensors will be stored and will be used to create new computational models allowing the responses and alerts of stress progressively reach more efficiency. We propose a new model of agriculture, where the plant indicates its real needs of resources, generating greater efficiency in the use of resources, avoiding wastes and generating increase of productivity. STRESSCAN is a technological solution under the IoT (Internet of Things) Internet concept of things, which aims to modify the relationship between people and plants, since understanding and taking into account plant metabolism in decision making is fundamental to production processes vegetable. (AU)

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