Agro tech: sensing use cases
Altice Labs
We develop innovative products and services for the telecommunications and information technology market.
Agriculture is changing, and innovation is more important than ever. Farming agriculture is facing huge challenges, from a labor shortage, supplies rising costs, and changes in consumer preferences such as food traceability and food safety. New precision agriculture and the implementation of developing technologies are extremely important to farmers, to maximize their yields by controlling important variables of crop farming, such as micro-climate changes, soil conditions, and moisture and fertilization levels.
Keep reading to learn more about a practical example of IoT sensing technology for the banana crop in Madeira Island or download the full white paper.
In Madeira Island, banana cultivation has a major impact in several areas, such as economic, social, and environmental, and in the region’s landscape, with its commercialization growing over time. Currently, the banana business moves millions of euros and employs thousands of people on the island. Since Madeira has many singular producers of bananas, there was a need to create an organization that manages the production, collection, and distribution of the banana to make it a sustainable and continued business.
The Banana Sector Management Company of Madeira Island (GESBA) was founded in 2008 to organize the banana production, processing, and marketing. The production suffers from seasonality, with seventy percent of the bananas on the island being produced in the summer, while only thirty percent are produced in the winter. Therefore, the large volume of production in the summer ultimately affects the market values. So, the company’s goal is to plan the yearly production, helping producers to ensure the sustainable use of resources and improving bananas’ quality and market value.
GESBA recognizes that new agriculture solutions are needed to face these challenges. In collaboration with the University of Madeira (UMa), Regional Agency for the Development of Research, Technology, and Innovation (ARDITI), and Altice Labs, GESBA is sponsoring an ongoing project named ‘BAnana SEnsing’ (BASE), approved and co-founded by PRODERAM 2020 ‘Programa de Desenvolvimento Rural da Regi?o Autónoma da Madeira’, Portugal 2020 and by the European agricultural fund for rural development (EAFRD), under the supervision of the Regional Secretariat for Agriculture and Rural Development (Government of Madeira). The BASE project started on 1 July 2022 and will end on 30 June 2023. This project will bring significant knowledge and technology innovation practices to the banana sector by applying sensor technology to monitor the banana crop production cycle in the field.
Using of IoT technology
The agrotech revolution is emerging and aims to use advanced precision technology, such as real-time analysis of soil nutrients and weather conditions with assistance of sensors to meet the future demands for food in a more sustainable, efficient, and eco-friendly way.
The internet of things (IoT) is remodelling agriculture, enabling farmers with a wide range of techniques, namely precision and sustainable agriculture, to face challenges in the field.
IoT technology enables the collection of weather information, such as moisture, temperature and precipitation, and soil conditions, such as nutrients and fertility, helping farmers improve yields and crop management.
There has been a significant rise in research and development of precision agriculture technologies to monitor pH, salinity, moisture content, organic matter, and texture. However, in situ monitoring of soil macronutrients, nitrogen (N), phosphorus (P), potassium (K), and other nutrients remains a challenge. Moreover, the sap flow sensors for banana plants are under the research domain.
The BASE project has deployed a set of IoT sensors in two sites with different climatic and edaphic conditions (parcels from the Ponta do Sol Processing Center and parcels from Lugar de Baixo Research and Experimentation Center sites), where the development of a representative sample of banana plants is monitored using morpho-agronomic traits during three phenological stages.
To perform these studies, the cultural practices, irrigation, and fertilization management of the banana plots are recorded in the field using a cloud monitoring platform.
The project has successfully implemented this platform, which is able to collect a set of data related with soil, weather, and plant parameters with near real-time updates that are also of extreme importance since the stored data can provide historical values of those parameters for future crop studies.
Having this technology applied to the field is of the utmost importance in understanding how to increase crop yield, especially under different weather and soil conditions.
High-level system architecture
The overall system architecture designed for the project is divided in four layers.
领英推荐
1.?????Sensors & data collection: In this layer, the system collects data from several types of sources. Banana plants have sensors to measure different parameters from air and soil, which communicate with the data storage & management layer through the gateway adapters using a SIM card with 4G mobile data.
2.????Data storage & management: This is the layer where the data is transformed and stored in Altice Labs’ Live!Data service platform. This platform consists of a backend server and a number of gateway adapters that communicate with the sensors, receive the data, validate it, and parse it into a format compliant with the database. The backend server exposes an API to retrieve and process the data, and to get analytics.
3.????Data visualization & consumption: Altice Labs’ Live!Green application, which runs on top of the Live!Data service platform, provides the user with a dashboard where it is possible to observe the last values read by the sensors, some historical information, and the geolocation of each sensor. In this dashboard, the user can compare the values read by the sensors over time and analyze the historical information to make the best decisions and learn from the collected data.
4.????Machine learning: This layer is responsible for recognizing patterns and getting hidden knowledge from the data stored on Altice Labs’ Live!Data platform, and for predicting events based on that data. This layer is where the user will obtain the benefits from the work and the investment in the previous layers (sensing, storing, and displaying the data). Data is read from the data storage layer and processed with adequate machine learning algorithms to retrieve knowledge from it. This layer is being developed in partnership with the University of Madeira (UMa), Interactive Technologies Institute / LARSyS and ISOPlexis.
Discover more about the architecture levels and the preliminary conclusions and future perspectives on our website.
Authors
?
Keywords: Connected home; Smart home; Matter; IoT
Contact us?if you want to engage in a deeper discussion on this topic!
Diretor Clínico na Clinica Medico Dentaria Quinta do Picado, Lda
1 年Helpful!