Agriculture can be considered a perfect field in which the main emerging technologies, such as cloud computing, artificial intelligence, IoT, robotics, and edge computing, can find immediate application quickly and on a large scale.
Innovating agriculture and food production systems is one of the most critical and complex challenges that modern society must face in the short term. The progressive increase of the world population and the consequent further erosion of already limited resources to meet billions of individuals’ increasingly elaborate and sophisticated needs could lead to the collapse of the entire system in the absence of a digital revolution capable of completely innovating.
It is, therefore, necessary to introduce tools, technologies, and solutions capable of reducing the environmental impact and automating production processes. They should make the complex and articulated agro-food chain efficient, streamlined, safe, and “traceable” to promptly provide everyone with healthy products, fast and at controlled prices.
Imagine the possibility of having a fleet of agribots capable of plowing fields, of drones capable of accurately mapping the territory and starting photo-interpretation processes. Think of animals interconnected with an operations center thanks to the Internet of Things, to self-driving tractors. Finally, picture a fully integrated system in which all the actors described so far coexist harmoniously. All these systems will rely on dependable and scalable operations on the cloud instead of traditional data centers.
Emerging Cloud Technologies in Transformative Agriculture: Case Studies
Grove Technologies AWS CEA
Let’s take a closer look at Grove Technologies who uses AWS to unlock multi-faceted solutions that offer insights into crop performance. Using AWS IoT Greengrass, they connected intelligent edge devices to the cloud, for instance, for anomaly detection in an expertly designed controlled agriculture environment. Their software and configuration can now be deployed and managed remotely and at scale without updating firmware.
Growers use wireless sensors placed in the fields for various tasks, including estimating agricultural parameters that are critical such as temperature, watering levels, and yield estimates.
By using AWS IoT Greengrass, the data is streamed into AWS IoT Core. Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB store ingested data using AWS IoT rules. Amazon Kinesis Data Streams are also used to batch and process incoming data. Technology is applied to send regular updates on crop/animal details, farm conditions, or weather.
The Solarfertigation project, to which three universities have contributed in various capacities, indeed represents an important example of collaboration and strategic partnership between the private sector and the public administration.
Cloud operations and solutions helped to ensure a lower consumption of water resources and fertilizers by integrating a software module to support the farmer’s decisions. Systems were deployed capable of concretely implementing the identified solutions based on analyzing the data from the network of “intelligent” sensors.
Fascinating is their integration of a photovoltaic system, which makes the product energy self-sufficient and allows farmers to arrive even in areas of their land not served by electricity. Furthermore, the system is equipped with an automatic module for the dosage of fertilizers to manage different crops in different parts of the same field.
To continuously improve irrigation activities and calibrate them based on soil conditions. Solarfertigation also allows farmers to collect environmental data from the field, integrate with meteorological information and develop the correct fertigation solution to increase the productivity of the land, simplify the management of the field and recover fertile areas.
Accenture hybrid Agri cloud integration
A different approach is based not on specific “vertical” applications but aimed at guaranteeing a “holistic” vision of an agricultural company. This approach is adopted by the famous multinational Accenture, which has implemented a service to overcome the transition period towards digital.
Farmers get to manage multiple IT tools and solutions separately to start a new era in which technology does not produce sectorial information but coordinates the entire activity through a series of correlated actions based on the data collected and processed in real-time.
Specifically, Accenture’s goal is to help farmers make data-driven operational decisions to optimize yield and increase revenue by minimizing expenses, crop failure chances, and environmental impact while increasing profitability. Total of an estimated $ 55 to $ 110 per acre.
The digital agriculture service by Accenture, in particular, aggregates granular data in real-time from multiple heterogeneous sources such as environmental sensors. It combined data from images obtained by remote sensing (which show the stress of the crop before it is visible to the naked eye), “equipment from the field,” meteorological information, and soil database supported on different clouds.
Many customers today seek to leverage the cloud’s never-ending storage capacity and strong compute abilities.
Agro-tech like many other industries processes incredible amounts of data from their sensors and devices and what can be better than storing them in an available & durable manner like the cloud? We recommend using S3 for object storing and the ability to run queries on the data with services such as Amazon Athena. You can set up integration with Sage Maker to build and train models based on that data and many more applications, helping you leverage the cloud storage and ML pre-built tools.
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