What are the advantages and disadvantages of IoT in agriculture?

advantages and disadvantages of iot in agriculture

There are many advantages and disadvantages of IoT in agriculture. IoT devices can have several benefits. But, they can have some serious demerits too. Check out the advantages and disadvantages of IoT in agriculture.

Advantages of IoT in agriculture:

Here are the top 5 advantages of IoT in agriculture.

Advantage 1: High productivity

IoT devices will increase the production in agriculture. Farmers place IoT devices all over the field. They can monitor better. As a result, more production. The practice of precision agriculture has been enabled by the advent of GPS and GNSS. Therefore, the farmer’s and/or researcher’s ability to locate their precise position in a field allows for the creation of maps of the spatial variability of as many variables as can be measured. Therefore, sensors collect these arrays consist of real-time sensors that measure everything from chlorophyll levels to plant water status, along with multispectral imagery. After that, we use this data in conjunction with satellite imagery by variable rate technology (VRT) including seeders, sprayers, etc. to optimally distribute resources.

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Advantage 2: Smart farming

Smart farming is done by placing IoT devices and gather data in agricultural farms. Using soil maps, farmers can pursue two strategies to adjust field inputs:

  • Predictive approach: based on analysis of static indicators (soil, resistivity, field history, etc.) during the crop cycle.
  • Control approach: information from static indicators is regularly updated during the crop cycle by:
    • sampling: weighing biomass, measuring leaf chlorophyll content, weighing fruit, etc.
    • remote sensing: measuring parameters like temperature (air/soil), humidity (air/soil/leaf), wind or stem diameter is possible. As a result, let us thank to Wireless Sensor Networks and Internet of things (IoT)
    • proxy-detection: in-vehicle sensors measure leaf status; this requires the farmer to drive around the entire field.
    • aerial or satellite remote sensing: multispectral imagery is acquired and processed to derive maps of crop biophysical parameters, including indicators of disease. Similarly, airborne instruments are able to measure the amount of plant cover and to distinguish between crops and weeds.

On the other hand, decisions may be based on decision-support models (crop simulation models and recommendation models) based on big data. But, in the final analysis it is up to the farmer to decide in terms of business value and impacts on the environment- a role being takenover by artificial intelligence (AI) systems based on machine learning and artificial neural networks.

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It is important to realize why PA technology is or is not adopted, “for PA technology adoption to occur the farmer has to perceive the technology as useful and easy to use. However, it might be insufficient to have positive outside data on the economic benefits of PA technology as perceptions of farmers have to reflect these economic considerations.

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Advantage 3: Smart management

Farmers can create smart management system by placing IoT devices. This is a very big advantage of IoT in agriculture. As a result, this can help farmers think less about stock management. We can offer IoT intelligence at three levels: IoT devices, Edge/Fog nodes, and Cloud computing. The need for intelligent control and decision at each level depends on the time sensitiveness of the IoT application.

For example, an autonomous vehicle’s camera needs to make real-time obstacle detection to avoid an accident. This fast decision making would not be possible through transferring data from the vehicle to cloud instances and return the predictions back to the vehicle. Instead, all the operation should be performed locally in the vehicle. Integrating advanced machine learning algorithms including deep learning into IoT devices is an active research area to make smart objects closer to reality. Moreover, it is possible to get the most value out of IoT deployments through analyzing IoT data, extracting hidden information, and predicting control decisions. A wide variety of machine learning techniques have been used in IoT domain ranging from traditional methods. For example, regression, support vector machine, and random forest to advanced ones such as convolutional neural networks, LSTM, and variational autoencoder.

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Advantage 4: Time saving

As we have discussed earlier, famers can manage inventory easily. It saves a lot of time.

Advantage 5: Better monitoring

Weather monitoring is easy using IoT. So farmers are less worried about their crops.

Disadvantages of IoT in agriculture:

You have already read advantages of IoT in agriculture. After that, here are the top 5 disadvantages of IoT in agriculture.

Disadvantage 1: Money needed

IoT devices need much money to implement. It needs a lot of space to implement these devices. That costs a lot. In the Internet of things, the precise geographic location of a thing—and also the precise geographic dimensions of a thing—will be critical. Therefore, such as its location in time and space, have been less critical to track because the person processing the information can decide whether or not that information was important to the action, and if so, add the missing information (or decide to not take the action). (Note that some things in the Internet of things will be sensors, and sensor location is usually important.)

The GeoWeb and Digital Earth are promising applications that become possible when things can become organized and connected by location. However, the challenges that remain include the constraints of variable spatial scales, the need to handle massive amounts of data, and an indexing for fast search and neighbor operations. In other words, in the Internet of things, if things are able to take actions on their own initiative, we can eliminate this human-centric mediation role. Thus, the time-space context that we as humans take for granted must be given a central role in this information ecosystem. Just as standards play a key role in the Internet and the Web, geospatial standards will play a key role in the Internet of things.

Disadvantage 2: Costly internet

Internet is not cheap at all. IoT devices need internet.  So that, we can monitor data. Internet access is limited by the relation between pricing and available resources to spend. Regarding the latter, we estimate that 40% of the world’s population has less than US$20 per year available to spend on information and communications technology (ICT).

In Mexico, the poorest 30% of the society counts with an estimated US$35 per year (US$3 per month) and in Brazil, the poorest 22% of the population counts with merely US$9 per year to spend on ICT (US$0.75 per month). On the other hand, from Latin America, we know that the borderline between ICT as a necessity good and ICT as a luxury good is roughly around the “magical number” of US$10 per person per month, or US$120 per year.This is the amount of ICT spending people esteem to be a basic necessity. Current Internet access prices exceed the available resources by large in many countries.

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Disadvantage 3: Weather effect

There are many impacts of IoT devices in weather. Above all, in agriculture. A concern regarding Internet-of-things technologies pertains to the environmental impacts of the manufacture, use, and eventual disposal of all these semiconductor-rich devices. Modern electronics are replete with a wide variety of heavy metals and rare-earth metals, as well as highly toxic synthetic chemicals. This makes them extremely difficult to properly recycle. Electronic components are often incinerated or placed in regular landfills. Furthermore, the human and environmental cost of mining the rare-earth metals that are integral to modern electronic components continues to grow. This leads to societal questions concerning the environmental impacts of IoT devices over its lifetime.

Disadvantage 4: Security problem

IoT is all about connection with internet. As a result, it evades the privacy. Event-driven smart apps control IoT systems. They take as input either sensed data, user inputs, or other external triggers (from the Internet) and command one or more actuators towards providing different forms of automation. Examples of sensors include smoke detectors, motion sensors, and contact sensors. Examples of actuators include smart locks, smart power outlets, and door controls. In other words, popular control platforms on which third-party developers can build smart apps that interact wirelessly with these sensors and actuators include Samsung’s SmartThings, Apple’s HomeKi.

A problem specific to IoT systems is that buggy apps, unforeseen bad app interactions, or device/communication failures, can cause unsafe and dangerous physical states, e.g., “unlock the entrance door when no one is at home” or “turn off the heater when the temperature is below 0 degrees Celsius and people are sleeping at night”. Therefore, detecting flaws that lead to such states, requires a holistic view of installed apps, component devices, their configurations, and more importantly, how they interact. Recently, researchers from the University of California Riverside have proposed IotSan, a novel practical system that uses model checking as a building block to reveal “interaction-level” flaws by identifying events that can lead the system to unsafe states. They have evaluated IotSan on the Samsung SmartThings platform. From 76 manually configured systems, IotSan detects 147 vulnerabilities (i.e., violations of safe physical states/properties).

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Disadvantage 5: Complexity

IoT devices can be complex to set up. Many famers don’t know this new technology. In semi-open or closed loops (i.e. value chains, whenever a global finality can be settled) the we consider IoT as a complex system due to the huge number of different links, interactions between autonomous actors, and its capacity to integrate new actors. At the overall stage (full open loop) it will likely be seen as a chaotic environment (since systems always have finality).

As a practical approach, not all elements in the Internet of things run in a global, public space. We implement subsystems to mitigate the risks of privacy, control and reliability. For example, domestic robotics (domotics) running inside a smart home might only share data within and be available via a local network. In other words, managing and controlling a high dynamic ad hoc IoT things/devices network is a tough task with the traditional networks architecture.

In conclusion, we have discussed about advantages and disadvantages of IoT in agriculture. Hope you enjoyed our article.

You can check out our article: use cases and impact of IoT in agriculture

Also check: challenges of IoT in agriculture

You can check out about IoT here.

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