Improving farming with AI, ML and IoT

How advanced technologies are creating a positive impact in crop production and fostering sustainable crop production practices and how farms can approach digital transformation efficiently.

According to estimates published by the UN, food production should be increased by at least 70% by the year 2050, in order to meet the food requirements for the projected 9.7 Billion people estimated population. However, resources are already limited, and current agricultural systems are increasingly degrading land, water, biodiversity and climate globally. Most governments and institutions recognize that there needs to be a balance between agricultural activity, food security and environment protection, in other words, more strategy and actions are required to create sustainable agriculture practices.

More pressure and higher expectations are being set for the agricultural industry to keep producing more and better food, while caring and making good use of the planet’s resources. There is no doubt that this industry plays a crucial role in most Countries, even acting as the backbone of the economy; not only providing food and raw materials, but also employing an important portion of the population.

To be successful in agriculture, farmers must focus their efforts in optimizing production per acre, minimizing operational costs, reducing risk of crop failure, and selling for the highest price as possible. This requires effective management of agricultural inputs (water, fertilizers, seed types), specialized knowledge of the field (soil fertility and plant development) and being able to adapt to unpredictable events such as sudden changes in weather and pests.

However, even with the use of technology and if improperly applied, farmers risk of getting poor results, having inaccuracies and bias to the management of a field. For example, sensors mounted in field equipment, existing weather stations and manual crop inspection techniques, sometimes do not provide real-time insights, or a complete view of the field behavior. Farmers face a bigger challenge as they need to make operational decisions based on a myriad of variables to optimize production, control crop quality and maximize revenue.

Over the past few years, the agricultural industry has been gradually adopting the use of advanced technologies such as artificial intelligence (AI), machine learning (ML), internet of things (IOT) and data analytics (DA) for innovative and creative solutions to increase yield, optimize resources and improve disease and pest control. Digital technology is also improving operations with automation and workload reduction and a wide range of other agriculture-related applications in the supply chain.

Maximizing the benefits is key when implementing advanced technologies. Data aggregation, integration and advanced analysis are aimed to produce intelligent insights and recommendations for farmers that allow them to control operational costs and make better decisions to increase yield and crop quality, while developing a sustainable management of natural resources and the environment. Depending on the crop, the technology stack, and level of data integration, Smart Technologies could yield savings of up to 75% in fertilization costs alone, 10% reduction in fuel use, and a 66% increase in productivity of the technical and field workforce.

Benefits of Advanced technologies in farming and agriculture.

The proper use of advanced technologies could be a game-changer in agriculture. Some of the benefits of incorporating AI, ML, IoT and DA in agriculture include the following:

Cost and resources optimization: with the application of IoT, farmers can operate and monitor devices and equipment more effectively. Benefits include the optimized use of equipment, preventive maintenance and reduction of machinery down time. As more devices and connectivity gets developed, the internet of things will continue to help farmers reducing effort and time spent on day-to-day activities.

Operational efficiency: Data collection and advanced analytics via artificial intelligence and machine learning provide useful information for agricultural applications to help in the early prevention, detection and spread of diseases, optimizing the use of water and fertilizer, which in time helps to foster a more sustainable farming operation.

Enhanced Weather Conditions Prediction: Combining satellite imagery, weather station data and models from various sources, machine learning models can help identifying fire outbreaks conditions and impact from sudden weather changes. As open data comes more available, organizations providing various weather monitoring can integrate more information creating better models in real-time.

Asset management: Automation, IoT and connectivity technologies provide farmers with the ability to monitor their assets in real time which helps with equipment usage optimization and even mitigates machinery and tools theft which is a big problem in some rural areas.

Current trends in Farming and Agriculture.

Precision Agriculture.

 Precision agriculture encompasses a set of technologies and practices that enable a more controlled and monitored operation in crop production. A combination of advanced technologies including, the internet of things, artificial intelligence, machine learning and data analytics, facilitate the use of a wide array of items such as automated guidance, control systems, robotics, drones, autonomous vehicles and advanced data analytics among others, which can provide any farming operation with tools to optimize production and reduce costs.  Benefits from the implementation of these technologies in the farm include optimized irrigation, precise application of fertilizers and pesticides and automation of repetitive tasks. On top of the economical benefits, precision agriculture also fosters sustainable farming by promoting a better use of water and soil additives and improving the performance of machinery which contributes to less consumption of fossil fuels. Some precision agriculture technologies that are revolutionizing farming include the following:

Sensors: Sensors can be deployed to detect soil, moisture and plant conditions. Combining Digital and Mechanical sensors is a good example of sensing innovation in agriculture. Mechanical sensors operate based on leaf contact and can be used to measure crop water potential that is, the relative changes in the leaf’s turgor pressure. Below is an example of a water potential sensor installed on a lemon tree.

As shown on the picture, the leaf is placed between two magnets which measure the difference between plant turgor and magnetic pressure. Low plant turgor increases magnetic pressure thus indicating that the plant lacks sufficient water and therefore notifying the farmer that irrigation is necessary. With the use of these sensors, farmers can track and measure the changes of leaf turgor in real-time providing deep insights about plant’s status.

Digital Imagery:  Satellite imagery and drones have been tagged as the precision agriculture heroes since they provide farmers with a myriad of functionalities in the farm, providing unparalleled perspective of the land, sky surveillance for data collection, security surveillance, spraying of herbicides and insecticides etc.

The picture above shows a drone flying over a hilly plantation of nuts in Hainan, China. The hilly terrains of Hainan account for 95% of the crops in the country. Before the introduction of drones in this area, farmers used to construct 10m-high poles which they would hold while spraying onto the nuts up high. These chemicals would drip down from the trees exposing farmers to toxic chemicals and as if not enough, the method was not effective in the control of diseases. The steeper the slope, the more dangerous it is for the farmers to spray their crops. With the introduction of autonomous drones, farmers can now effectively control diseases and also easily survey their farms located on steep slopes.

Drone technology frees farmers from labor intensive activities to focus on adding value. Hainan China is a radical example of how drones are revolutionizing agriculture, but this technology is being used consistently for different purposes in agriculture across the world.

Big data analytics.

Data is improving how farmers perform their operations. Farmers can collect massive amounts of data of their operations from machinery, weather stations, open data sources, third party vendor applications, sensors and IoT devices. With the right expert advice, it is feasible to put in place a data centric solution where all the available data can be integrated and analyzed using machine learning algorithms to extract key insights on the farm status. A well designed Smart system, can make personalized recommendations on various aspects of crop production increasing yield and saving costs.

Challenges of using advanced technologies in agriculture.

One of the main challenges affecting the adoption of advanced technologies is the segregation of the information and the siloed, discrete approach that most digital applications generating data adopt. To tackle this challenge, incorporate a data integration service provider, that can work agnostically from the technology to help you with data integration and advanced analytics, getting the most of your data. This will prevent you from becoming highly dependent on multiple technology consultants which at the end makes digitization expensive and less effective.

Another challenge relates to device connectivity and efficient use of power in smart devices. Sensors and gadgets are a great solution, as long as they can access a network and have access to a power source. As batteries become more efficient and solar power harnessing solutions are improved, sensors and other electronic components are becoming more power efficient. With the incorporation of edge computing (the capacity of running routines at the component level) sensor are becoming more intelligent and capable of processing information on their own and on the spot. These technologies will keep improving providing more and better options to farmers.

How to incorporate the use of advanced technologies successfully in Farming

The adoption of technologies for sustainable farming systems can be overwhelming with so many options available. Farmers need to identify the appropriate pieces of technology to incorporate into their farming operations, focusing on what really provides rapid improvement on crop yields and production cost optimization specific to their operation.

Farmers need expert advice, for the adoption and implementation of appropriate advanced digital technologies. A good approach is getting support from an agnostic technology integrator with advanced data analytics capabilities, to unbiasedly help you minimize implementation costs while integrating data from the any disjointed technology assets you already are using in your operation.

Ignoring the opportunity that technology offers for farmers is not an option as more and more globalized agricultural supply chains create more competitiveness and smaller margins in agricultural production.

Talk to us today on how we can help with your Farm Digital Transformation Journey.