Tag: Digital Agriculture

The widespread benefits of the Internet of things (IoT) do not end with the health, manufacturing, automotive, aerospace and aviation industry alone; the agricultural sector is not left out. IoT has revitalized the way things are done in the agricultural sector by creating environmentally sustainable operations, transforming ideas and bringing new opportunities at an unimagined scale.

Thanks to the impact of digital twins in farming, low yield and productivity, the spread of pests and diseases and unsustainability have become things in the past.

How do digital twins mitigate these rooted problems associated with agriculture? To answer these questions, let’s find out the meaning of digital twins and why it is introduced to the agricultural sector?

The high complexity of field-based processes in agricultural crop production places considerable demands on the development of robust technologies about the variability of the plants, the soil, the technologies, the environment and numerous disturbance variables.

Simulations of specific aspects have supported these developments for many years. A holistic simulation of the agricultural process – a “digital twin” so to speak – with the integration of as many of the listed influencing variables as possible has considerable potential.

In particular, the influence of individual variables on the overall process can be used for error analysis, service or new developments.

What is Digital Twinning or Digital Twins?

Digital twins are the virtual replica of a real-life asset (whether material or immaterial) created to test, predict and understand the behavior of its physical counterparts.

Digital twin in agriculture represent real objects where historical objects can be reproduced and future objects simulated to create scenarios for farmers to act on.

It empowers farmers and stakeholders to deal with unexpected deviations, for example by identifying problems in advance, scheduling predictive maintenance at the right time and providing instant solutions for compounding problems. Digital Twins speeds up the agricultural business from production to marketing and sales.

How is this possible?

For example, let’s say crop production is affected by pests and diseases in a region. By adopting it, you can gather quality information human senses can’t observe through a mobile app that works as a digital counterpart using sensors and satellite data.

You can then provide images of affected plants and describe the problem, then compare these images with the replica of that exact plant and provide solutions. That’s simply how digital twins work.

Conditions required for digital twin in agriculture

1. Individuality

The digital twin in agriculture has to be specific, with a specific name given as opposed to the general name of goat or cat.

2. Near Real-Time

This means for as long as the real-time exist the twin should also exist

3. Data-Informed

It has to be digitally measured, with the same instrument for the real sample.

4. Realistic and Actionable

The digital twin in agriculture has to be close to the real thing in properties and form. It has to be realistic.

5. Actionable

Information regarding the real thing should be action bound.

How it works?

It utilizes technological equipment such as sensors, satellites, and other devices to monitor the digital twin. With this information gotten historical data can access when needed and is required to make plans.

It involves the overall process of the digital twin.it is not necessary to be a fancy arrangement, it is only required to get them done at the right time it just has to be scientific realistic.

How They are Different From Models?

Models are just a representation of a particular thing, unlike digital twins the models are not only a representation but are also incorporated in the process of the real thing for a measurable output. Most models often give wrong results. When they are combined they also give false reports.

They are used for specific purposes. Their result can be seen in terms of dozens. This is to ensure the reliability of the results. They ensure the user is protected from the complicated technicalities by presenting information in a way that is easy to understand. It should present the status updates on the real thing.

How To Interact with digital twins?

It is monitored on the devices such as laptops, tablets or phones. It makes it easy for you to access the history or predict the future of the real thing. You can also work with the system to switch on physical systems like irrigation.

The inner functionality of the digital twin in agriculture is hidden and the user does not need to understand the complexities. It only exposes the user to what is required in physical dealing. Although features that can not be assessed in normal dealing are added.

Where am I likely to see digital twins in agriculture?

The use of the digital twin has already taken off. It is used in the monitoring of livestock both physically and remotely. Field monitoring system ensures the report of field state and crops for better and informed management decisions. The remote monitoring system reports the state of farm machinery like a planter, tractor, sprayer, etc. For early detection and pre-emotion of faults.

The real-world thing is modeled realistically and life reports have meaning on the state of the system. It has some limitations, the thing monitored can only be checked for a single aspect of the thing. It is used in other industries but it is used in Agriculture to cover several properties because of the diversity in the farm.

Conclusion

Before the technological age, research and development were carried out to understand and anticipate plants’ behavior to combat major agricultural problems which are the spread of pests and diseases and low productivity. Due to the use of crude tools, the research outcome was unverified and the results were unreliable. Hence, the problems persisted.

Then, agriculturists had no other way of experimenting with plants behavior except by trial and error method resulting in abundant loss of resources and time. To end these farming mysteries, digital twins in farming were introduced to give a detailed understanding of plant and animal behaviors to improve farming efficiencies. Those most enthusiastic about the technological revolution expect that agricultural operations will experience substantial benefits through these advances.

So, no one can understand your physical land better than you do…and data science. And GeoPard in that case is a useful Platform for Growers that helps to:

• Collect technical data insights via remote sensing, soil sampling, sensors, topography, etc.
• Have any minute field access with satellite monitoring and crop rotation data.
• Manage your data even when offline with the app.

Allowing communication between machines and various hardware, and inserting digital intelligence into devices, enables to the connection of a vast number of physical devices and sharing of data through the internet without human intervention.

Basically, the term ‘IoT’ includes everything connected to the internet, however, it is increasingly being thought of as pertaining to objects that ‘talk’ to each other. This can include everything from simple sensors to smartphones, wearables, and computers – but for devices that are all connected together.

When connected devices are combined with smart software, as in many automated systems, it is possible to do much more than just gather information but to analyze topography, soil, and crop yield and initiate some action, including learning from a process.

The IoT can apply equally to devices on closed private networks, but the concept of the Internet of Things brings those networks together, creating a much more connected world.

There are many devices that are part of the IoTs, which allow the monitoring of entire processes of agricultural production. IoT devices, supported by software systems, can monitor processes from seedling production through crop management (irrigation, plant protection, and plant nutrition) up to post-harvest.

These devices and software systems allow primary production to be seamlessly connected and integrated into other phases in the agricultural value chain – such as processing, wholesale, retail, and even the final customer.

Most of the IoTs implemented in agricultural production are in the form of sensors that provide relevant data about the real situation in the fields, and the greenhouses, allowing us to make crop monitoring at any time, or in the context of animal production, the status of the individual animal.

These sensors are capturing or generate various types of data, and mostly they capture environmental parameters (humidity and temperature of the soil and air, electrical conductivity, precipitation, wind velocity and direction, leaf wetness, irradiation, and many other implementations specific to the needs of the growers).

What are the opportunities of Iot in agriculture?

The increasingly negative effects of climate change that we are witnessing in the recent period are disrupting agricultural production, bringing up the need for taking well-informed and adequate decisions in a very short period of time.

In addition to this, but totally another perspective, is the following of the strict legal framework and correct record-keeping process, where the producers are losing too much of their precious time. In the context above, the implementation of IoTs across the farm and agricultural operation can help solve one of the main issues of the modern farmer.

The IoTs in agriculture can help the farmers in getting insights about the conditions in the agricultural productions in real-time. They also can help feed the decision-support software for generating proper advice in the decision-making processes.

Additionally, all of the recorded data can be later used as proof for every operation that is made and all of the inputs that are applied, allowing the farmers to not spend additional time in crunching numbers which extensively alleviates the record-keeping process.

Specifically, the implementation of IoT in agriculture can shorten the time in checking the farm routine activities, monitoring specific operations and statuses and allowing the farmers to focus on important activities such as strategic management and positioning of the products on the market.

The end result of IoTs is the potential increase in productivity, cost reduction in input application, traceability, and less labor.

How does IoT work in agriculture?

The IoT implementation on-farm can help the farmers to cut their costs by applying inputs that are more accurate in quantity, just from the interpretation of the information generated on the fields.

With the IoTs data, the farmers can run different models for detecting disease and pest occurrence, directly influencing the number of applied pesticides and the number of executed operations that will ultimately lead to saving time, cutting costs, and putting less impact on the environment.

Additionally, by calculating the evapotranspiration with the help of the generated IoT data, the farmers will have an opportunity to timely schedule their irrigation patterns allowing them to minimize the applied water.

Saving irrigation water is extremely important in places where there is water scarcity. In addition, the data needed for executing such an operation can be managed with the implementation of several IoT sensors mentioned above.

Apart from crop production, the IoT technology in agriculture is also very useful in livestock management, where the costs for raising livestock are rising from moment to moment. Lately, in livestock management, a great accent is put on how the farmers are treating the animals and different concerns sides are pushing the farmers in to threaten the animals in a more humane way.

The implementation of IoT allows farmers to attach different sensors to the animals without making any kind of discomfort, thus giving them away to constantly monitor their health and activity status.

There are a lot of types of data that are measured through the IoTs, such as animal heart rate, blood pressure, ruminating time, body temperature, etc. Additionally, there are sensors that can be found on the market that are transmitting GPS data. Location monitoring is very useful to farmers who have open-range pastures.

Utilizing all of the above-mentioned types of data is giving the farmers enough time to be proactive about their operations resulting in increased productivity, lowering the negative impact on the environment, and mitigating the negative effects of climate change.

How to use IoT in agriculture?

The advantages of IoT in agriculture can be many, mainly because of their wide-ranging applications. In order to gain a more complete picture of the importance of IoT in agriculture, we are going to mention several types of IoT applications in different types and phases of agricultural production:

1. Weather stations

Sensors combined within weather stations collect data providing measurements that map climate conditions, inform crop decision making, and potentially help to improve crop capacity, delivering maximum possible yields.

By measuring these environmental factors, and generating data from them, the IoTs can build up a precise history that can help farmers with their decision-making processes, or make probabilistic-based plans, thus lowering the risk of unexpected costs and operations.

2. Greenhouse automation

Weather stations are not only used for collecting necessary environmental data but can also be used to automatically adjust conditions in controlled microclimate conditions, such as greenhouses, to match specific growing parameters.

Whether the use is for hydroponics or substrate-grown plants, the benefits of automated greenhouses can be significant. Instantaneous data obtained by the sensors can be combined to give a broad picture of the conditions in the greenhouse.

If the optimal parameters for optimal growing conditions are known and set, automatic adjustment of the environment is readily achieved.

3. Crop management devices

There is a large range of sensors that can be placed in the field to collect decision-making information such as temperature, precipitation, crop health, crop nutritional state, and many others. These devices are core elements in precision farming.

From the sensor measurements, many forms of valuable data can be obtained. When that data is stored, it creates a temporal history that feeds into the decision-making software that helps the farmers in their decision-making processes.

4. Livestock management devices

Sensors can be applied, or even attached, to animals to provide information on the temperature, health and nutritious insight of each individual animal, as well as overall information about the herd.

With this kind of sensor, the farmer knows exactly where specific animals with unique identifiers are. The sensors can also provide information such as when a specific animal last ate, slept, walked, etc.

5. Farm productivity management systems

There are many potential systems that monitor and control all sensors installed in the field, combining them to provide a powerful analytical dashboard for logistics, accounting and reporting functions.

By knowing the exact inputs and outputs used across the farm, farmers can obtain a clear of potential risks that they might face but have information to hand to help with formulating optimal solutions.