Launch of IoT and artificial intelligence to increase the competitiveness in Swedish apple and grapevine production

• A more globally sustainable management of the horticulture and agriculture industries has high priority and should be available by using new technology. The programme EIP-Agri Sweden (European Innovation Project, Agri in Sweden) has approved a project to develop such an innovation based on new technology. The innovation is a first stage of a decision support solution (or system) to be able to achieve a sustainable and competitive production of fruit and wine. The innovation will be based on tools like sensors, information and communication technology (ICT) and artificial intelligence (AI) to, for example, increase and optimize harvest yield, reduce environmental and climate impact, and decrease labour costs. The results will be included in a platform that can be adaptive in the future to other crops like for example raspberries and strawberries. A digital assistant for field production is planned in the first stage to be developed. A fine meshed network of connected sensors collects climate and other data and sends them over an IoT network to a cloud system. A machine learning system (ML) uses these data together with manual observations of the crop phenological stages during the season, as well as measurements taken by the producers. Examples of manual observations are plant diseases, nutrient deficiency. The machine learning system will work as a Digital Assistant for the producer. Gives, for example, diseases prognosis, nutrient demands, irrigation and optimal dates for harvest, as well as yield quality at harvest. The work in the project is carried out by a cross functional team consisting of producers, experts in food, agriculture and horticulture, measurement-, digitalisation of Food systems, software/system-, marketing-, and AI/ML-experts. Initial progress and results are reported and discussed in this paper. 

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

LANTBRUKSVETENSKAPER  -- Lantbruksvetenskap, skogsbruk och fiske -- Trädgårdsvetenskap/hortikultur (hsv//swe)

AGRICULTURAL SCIENCES  -- Agriculture, Forestry and Fisheries -- Horticulture (hsv//eng)

Keyword

Decision system

Digital assistant

Phenology

Sensor network

Publication and Content Type

ref (subject category)

kon (subject category)