SMART FARMING
SMART FARMING
Agriculture is one of the oldest industries. Whatever is said, but to engage in self-development you have to eat well first. In order for us to be able to eat something at the computer while coding a smart application, someone has to grow and cook food. Therefore, the rapid development of agriculture is obvious. It is the industry, in which many startups, smart devices and technology are used to facilitate and speed up the process of getting products to our tables.
"Smart farming" (digital farming) is a new concept that applies to farm management using technologies such as Internet of Things, robotics, drones and artificial intelligence in order to increase the quantity and quality of products as well as optimize the needed human resources required for production. The Internet of Things has provided ways of improving almost every industry.
The main purposes of the usage of technology are process automation, obtaining more accurate and faster data, the ability to calculate needs and opportunities, environment friendly production, better management and logistics.
Even though the Smart farming is becoming more and more popular nowadays, the speed of its implementation is influenced by many factors:
- The influence of smart things and their effectiveness in the agricultural industry has not been sufficiently proved.
- A lot of new devices have not passed long-term testing.
- The conservative views of farmers.
- The poor Internet connection in remote areas, which makes the usage of IoT impossible.
- Compatibility among manufacturers.
- Data protection and data sovereignty.
- The quality of algorithms used in farm management systems.
- Low media competence of farmers.
SMART IOT-BASED AGRICULTURE CYCLE
The devices have to collect and process data in a repetitive cycle in order for farms’ operation to be optimized. The data from these devices is transmitted through the Internet. This allows farmers to respond to problems, changes in environmental conditions or obtain statistics instantly.
Smart farming follows this cycle:
- Observations. Sensors record data from observations of crops, livestock, weather, air and soil. They keep the statistics.
- Diagnosis. The information arrives at a cloud-based IoT platform. Rules and models of decisions-making, called “business logic” are determined in advance. They determine the condition of studied objects and identify its drawbacks and needs.
- Solutions. Once a problem has been identified, machine learning-driven IoT components make a decision whether to fix the problem and if so, how to solve it.
- Action. The cycle is repeated from the beginning after evaluation and action of the end user.
This chart shows the amount of fresh vegetables produced in the United States from 2002 to 2008. The figures are considerable and remain almost on the same level. This demonstrates the need of the latest technology and smart farming for agriculture at least to make a breakthrough.
What are the main areas for appliance IoT in agriculture?
IoT agricultural solutions consist of several monitoring, controlling and tracking programs that measure several types of variables, such as air monitoring, temperature monitoring, humidity monitoring, soil monitoring, water monitoring and controlling, fertilization, pest controlling, lighting control and location tracking. Most research focuses on monitoring (70%), control (25%) and tracking (5%).
The scope of IoT can be classified in even more detail. This information can be useful for people who are going to create applications and devices for the agricultural sector. The figure shows the priorities and percentages of the usage of a particular sphere.
The Embrox team developed an agricultural device as well.
This device is used in fields during harvesting. Its main function is to identify pickers, harvest and pack time. All collected data is uploaded to the cloud.
CHALLENGES
- Recognize 8 small QR-codes with the least number of cameras
- Achieve a scan speed of 1.2 seconds
APPROACH
- The Embrox team decided to use the Raspberry Pi 3 Model B with the Arducam Multi-Camera Adapter in order to be able to connect a few cameras.
- We proposed the simplest approach based on a transistor switch in order to have the possibility to use an LED strip for capturing QR codes and turning LED strips off when light is not needed.
- The electrical engineering team developed a custom battery gauge and power PSB.
- The mechanical engineering team suggested using mirrors to reduce the device thickness.
- All cameras work in multithreading with async handling.
- The scanned data goes to the mobile application via BL connection. This data then gets to the server.
- Technology such as Raspberry Pi C++ Java QT Android iOS HTTP BLE NFC RestFull API AWS EC2 were used to create the application.
If you are looking for an idea for a startup, the agricultural industry is the best choice as a lot of technology is needed there. Here your work will definitely matter, because the need for food will always remain, no matter how the world will change.
Agriculture
Smart farming
Digital farming
IOT
Startup
Internet of Things
Robotics
Drones
Artificial Intelligence
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