Smart agriculture: IoT Technology is changing the way we farm
TagoIO Team
As the world’s population continues to grow, it is becoming increasingly vital for us to find innovative ways to produce food. Many governments around the world are already looking for new technologies that can improve their food production, especially after the pandemic. IoT (Internet of Things) applied to smart agriculture is one of the viable solutions to increase production, and it’s helping numerous agricultural areas by providing data from several sensors located throughout farms.
Application areas
Among the areas where IoT can help agriculture, there are:
Greenhouses: By utilizing IoT sensors to monitor various conditions such as temperature, humidity, and soil moisture, farmers are confident that their plants are healthy and have optimal growing conditions.
Fields: IoT sensors can map fields and track the location of crops to determine which areas of the field are doing well and which areas need improvement.
Farm asset management: IoT can help keep track of farm equipment and machinery. Farmers can use this information to plan for maintenance and repairs.
Improving irrigation: IoT can optimize irrigation systems by providing data on soil moisture levels, weather patterns, and more. This information can help farmers make better decisions about when to water their crops, how much water to use, and what type of irrigation systems to use.
Planting: IoT can also provide high levels of decision-making insight regarding when and where to plant crops. By understanding the data provided by IoT sensors, farmers can choose the best time to grow their crops and create optimal scenarios for success.
Pest control: IoT sensors can help identify areas of fields that have pests, helping farmers to take preventative actions to control the situation and protect their crops.
Weather: With the combination of IoT sensors with weather information, it’s possible to better understand what conditions the crops are in, as well as their future necessities. Farmers can then use this data to predict weather patterns and forecast crop yields.
Sensors and networks for smart agriculture
One of the most common challenges while transforming a non-smart farm into a smart one is where and how to apply technologies, as placing sensors and sending the data collected can be difficult depending on the environment.
Among the key places where you can put these sensors, some examples would be: on the soil, on the plants, in the silos, and so on. The type of sensor used will also depend on what information you want to track or measure.
A few notable sensor types include:
Dielectric Soil Moisture sensors to measure moisture levels,
Light sensors to track how much sunlight the plants are receiving,
Electrochemical sensors for soil nutrient detection,
Location sensors which are one of precision agriculture’s main components,
Mechanical Soil sensors to measure soil compaction,
Airflow sensors to measure soil air permeability.
These sensors must send the collected data to a central location where it can then be processed and analyzed. There are numerous ways to communicate this data, including cellular, LPWANs (LoRa, NB-IoT), satellites, and other methods. However, each of these has its own set of challenges; for example, in countries with limited access to coverage, cellular networks may not be the best alternative to pick. Similarly, satellite connections can be expensive or unreliable in areas with bad weather.
Use cases
Some notable use cases are already making a difference in the agricultural industry, here are some examples:
Precision agriculture: An approach to smart farming management that uses sensors and other technology to improve the efficiency of crop production. By understanding data collected from IoT sensors, farmers can make better decisions about when to plant their crops, how to water them, and what fertilizer to use. Smart Farms use this to improve yields and decrease the costs of production.
Agricultural drones: offer a cost-effective way to gather data about crops. Farmers can equip drones with sensors that measure various factors such as plant height, chlorophyll content, and soil moisture levels. Farmers can then use this data to improve crop yield and quality.
Connected silos: IoT-connected silos help track the grain level in each silo. Farmers can use this information to predict when the grain will run out and need to be replenished, allowing them to also use this data to understand patterns in grain consumption and optimize production accordingly.
One especially noteworthy case, showcasing the numerous capabilities of smart farming, is how the university of Rio de Janeiro PUC implemented a project that used IoT to improve the overall efficiency and yield of two farms. Their connected farm system collects data from sensors to guide decision-making for soil preparation, time of planting, foliar fertilization, monitoring of plant growth, assessment of plant health, correction of planting, and irrigation techniques — all of it being done with IoT.
Features and functions applied in smart agriculture
IoT systems offer many features and functions for smart agriculture. We will divide these into four main categories: data collection, data analysis, control systems, and service alerts.
Data collection: This is the process of gathering data from sensors and other sources. Farmers can use this data to understand trends and make decisions to improve the efficiency of agricultural production.
Data analysis: After collecting data, another essential part of the process is to analyze it. This data can be used to understand trends and make decisions to improve the efficiency of agricultural production.
Control systems: These systems can remotely control some assets and automate processes. For example, a control system might use data from a soil moisture sensor to automatically turn on an irrigation system when the soil moisture levels drop below a certain threshold.
Service alerts: It’s a form to communicate changes or events inside the farm that can be related to assets or production. For example, they can inform about changes in door status or soil moisture levels.
Ability to connect in multiple network types: IoT for smart agriculture is not only about the devices and applications used on the farm, it is also about the ability to connect to multiple network types: cellular, LPWANs (LoRa, NB-IoT), satellites, and others. This versatility allows farmers to choose the best network for their needs, whether they need coverage, reliability, or cost.
How can TagoIO help?
Maybe the easiest way to access these features is using an IoT platform, and that’s where TagoIO comes to assist you. Inside TagoIO’s cloud platform, users can collect, analyze, and take action based on data from multiple devices and locations. Users can also use on-premise solutions using TagoCore for farms with limited, unstable, or even inexistent connectivity.
TagoIO also works with multiple network types and has a long list of IoT devices for any application. A few examples of devices for smart agriculture that are ready to use would be:
Milesight EM500-SMT, a Soil Moisture, Temperature, and Electrical Conductivity Sensor over LoRaWAN,
The Dragino LSE01, a LoRaWAN Soil Moisture & EC Sensor for IoT of Agriculture,
Dragino LSNPK01, a LoRaWAN Soil NPK Sensor for IoT of Agriculture designed to measure nutrients,
Globalsat LT-10, a LoRaWAN compliant light solar tracker, usually used as a cattle tracker,
Tektelic Agriculture Sensor, which can measure soil moisture and temperature, air temperature and humidity, and outdoor light monitoring.
Besides these devices listed, we have a wide range of partners offering sensors for different needs in agriculture, making it easier to find the correct sensor for every situation. You can also check other devices already integrated in our devices page here.
What can we look forward to in the future of smart agriculture?
The benefits of IoT for smart agriculture are numerous, from precision agriculture to reducing costs and improving yields. In the future, we can expect to see more IoT applications as the technology becomes more affordable and accessible. We will also see a continued trend of IoT devices becoming smaller, more accurate, and more rugged to withstand the harsh conditions of the agricultural environment.
However, some people still believe that you need to be a computer expert to be able to implement IoT smart agriculture solutions, but that’s not true anymore. In the market, there are many easy-to-build smart farm applications, and you can learn more about them by looking at our Kickstarter; there you’ll find several applications for different areas of agriculture.
As the world’s population continues to grow, it is becoming increasingly vital for us to find innovative ways to produce food. Many governments around the world are already looking for new technologies that can improve their food production, especially after the pandemic. IoT (Internet of Things) applied to smart agriculture is one of the viable solutions to increase production, and it’s helping numerous agricultural areas by providing data from several sensors located throughout farms.
Application areas
Among the areas where IoT can help agriculture, there are:
Greenhouses: By utilizing IoT sensors to monitor various conditions such as temperature, humidity, and soil moisture, farmers are confident that their plants are healthy and have optimal growing conditions.
Fields: IoT sensors can map fields and track the location of crops to determine which areas of the field are doing well and which areas need improvement.
Farm asset management: IoT can help keep track of farm equipment and machinery. Farmers can use this information to plan for maintenance and repairs.
Improving irrigation: IoT can optimize irrigation systems by providing data on soil moisture levels, weather patterns, and more. This information can help farmers make better decisions about when to water their crops, how much water to use, and what type of irrigation systems to use.
Planting: IoT can also provide high levels of decision-making insight regarding when and where to plant crops. By understanding the data provided by IoT sensors, farmers can choose the best time to grow their crops and create optimal scenarios for success.
Pest control: IoT sensors can help identify areas of fields that have pests, helping farmers to take preventative actions to control the situation and protect their crops.
Weather: With the combination of IoT sensors with weather information, it’s possible to better understand what conditions the crops are in, as well as their future necessities. Farmers can then use this data to predict weather patterns and forecast crop yields.
Sensors and networks for smart agriculture
One of the most common challenges while transforming a non-smart farm into a smart one is where and how to apply technologies, as placing sensors and sending the data collected can be difficult depending on the environment.
Among the key places where you can put these sensors, some examples would be: on the soil, on the plants, in the silos, and so on. The type of sensor used will also depend on what information you want to track or measure.
A few notable sensor types include:
Dielectric Soil Moisture sensors to measure moisture levels,
Light sensors to track how much sunlight the plants are receiving,
Electrochemical sensors for soil nutrient detection,
Location sensors which are one of precision agriculture’s main components,
Mechanical Soil sensors to measure soil compaction,
Airflow sensors to measure soil air permeability.
These sensors must send the collected data to a central location where it can then be processed and analyzed. There are numerous ways to communicate this data, including cellular, LPWANs (LoRa, NB-IoT), satellites, and other methods. However, each of these has its own set of challenges; for example, in countries with limited access to coverage, cellular networks may not be the best alternative to pick. Similarly, satellite connections can be expensive or unreliable in areas with bad weather.
Use cases
Some notable use cases are already making a difference in the agricultural industry, here are some examples:
Precision agriculture: An approach to smart farming management that uses sensors and other technology to improve the efficiency of crop production. By understanding data collected from IoT sensors, farmers can make better decisions about when to plant their crops, how to water them, and what fertilizer to use. Smart Farms use this to improve yields and decrease the costs of production.
Agricultural drones: offer a cost-effective way to gather data about crops. Farmers can equip drones with sensors that measure various factors such as plant height, chlorophyll content, and soil moisture levels. Farmers can then use this data to improve crop yield and quality.
Connected silos: IoT-connected silos help track the grain level in each silo. Farmers can use this information to predict when the grain will run out and need to be replenished, allowing them to also use this data to understand patterns in grain consumption and optimize production accordingly.
One especially noteworthy case, showcasing the numerous capabilities of smart farming, is how the university of Rio de Janeiro PUC implemented a project that used IoT to improve the overall efficiency and yield of two farms. Their connected farm system collects data from sensors to guide decision-making for soil preparation, time of planting, foliar fertilization, monitoring of plant growth, assessment of plant health, correction of planting, and irrigation techniques — all of it being done with IoT.
Features and functions applied in smart agriculture
IoT systems offer many features and functions for smart agriculture. We will divide these into four main categories: data collection, data analysis, control systems, and service alerts.
Data collection: This is the process of gathering data from sensors and other sources. Farmers can use this data to understand trends and make decisions to improve the efficiency of agricultural production.
Data analysis: After collecting data, another essential part of the process is to analyze it. This data can be used to understand trends and make decisions to improve the efficiency of agricultural production.
Control systems: These systems can remotely control some assets and automate processes. For example, a control system might use data from a soil moisture sensor to automatically turn on an irrigation system when the soil moisture levels drop below a certain threshold.
Service alerts: It’s a form to communicate changes or events inside the farm that can be related to assets or production. For example, they can inform about changes in door status or soil moisture levels.
Ability to connect in multiple network types: IoT for smart agriculture is not only about the devices and applications used on the farm, it is also about the ability to connect to multiple network types: cellular, LPWANs (LoRa, NB-IoT), satellites, and others. This versatility allows farmers to choose the best network for their needs, whether they need coverage, reliability, or cost.
How can TagoIO help?
Maybe the easiest way to access these features is using an IoT platform, and that’s where TagoIO comes to assist you. Inside TagoIO’s cloud platform, users can collect, analyze, and take action based on data from multiple devices and locations. Users can also use on-premise solutions using TagoCore for farms with limited, unstable, or even inexistent connectivity.
TagoIO also works with multiple network types and has a long list of IoT devices for any application. A few examples of devices for smart agriculture that are ready to use would be:
Milesight EM500-SMT, a Soil Moisture, Temperature, and Electrical Conductivity Sensor over LoRaWAN,
The Dragino LSE01, a LoRaWAN Soil Moisture & EC Sensor for IoT of Agriculture,
Dragino LSNPK01, a LoRaWAN Soil NPK Sensor for IoT of Agriculture designed to measure nutrients,
Globalsat LT-10, a LoRaWAN compliant light solar tracker, usually used as a cattle tracker,
Tektelic Agriculture Sensor, which can measure soil moisture and temperature, air temperature and humidity, and outdoor light monitoring.
Besides these devices listed, we have a wide range of partners offering sensors for different needs in agriculture, making it easier to find the correct sensor for every situation. You can also check other devices already integrated in our devices page here.
What can we look forward to in the future of smart agriculture?
The benefits of IoT for smart agriculture are numerous, from precision agriculture to reducing costs and improving yields. In the future, we can expect to see more IoT applications as the technology becomes more affordable and accessible. We will also see a continued trend of IoT devices becoming smaller, more accurate, and more rugged to withstand the harsh conditions of the agricultural environment.
However, some people still believe that you need to be a computer expert to be able to implement IoT smart agriculture solutions, but that’s not true anymore. In the market, there are many easy-to-build smart farm applications, and you can learn more about them by looking at our Kickstarter; there you’ll find several applications for different areas of agriculture.
