Over the centuries, the Agricultural industry has been a playground of major transformations, with the latest being a shift toward automation. Though automation in agricultural farming is nothing new – machines have been used to help with planting, watering, harvesting, and other tasks for many years now, the recent advancements in automation, robotics, and artificial intelligence have made machines affordable, more reliable, and simpler than ever before.

Agricultural farming and the state of crop automation:

The Agricultural industry is one of the world's oldest and most important industries. It not only sustains human society but contributes significantly to the global GDP. The global agriculture market grew from $11,109.32 billion in 2021 to $12,152.6 billion in 2022 at a compound annual growth rate (CAGR) of 9.4%

However, the Agricultural industry is also one of the most labor-intensive industries in the world. In 2020, 19.7 million full-time and part-time jobs were related to the agricultural and food sectors, amounting to 10.3% of total U.S. employment. Though the employment statistics in agriculture have decreased due to industrialization and urban migration, farm wages and salaries account for significant production expenses for farm owners. According to the US 2017 Census of Agriculture, wages and salaries plus contract labor costs represented 12% of production expenses for all farms, reiterating a need to implement agriculture.

Challenges in the Agriculture Industry - The Need for Automation:

The agricultural industry needs to address the following issues and challenges for profitable outcomes and ensure food security for the future:

1. Climate Change: Unpredictable rains, floods, and season patterns make it hard to forecast weather, making it challenging for farmers to define irrigation and watering patterns.
2. Soil Degradation: Poor farming practices and the heavy use of chemicals have degraded the soil quality, reducing the quality and quantity of crop yields.
3. Pests and Plant Diseases: Overuse of pesticides has led to the development of resistant pests, resulting in newer and more challenging plant diseases. Identifying newer diseases and accessibility of fertilizers and pesticides is a challenge
4. Labor Availability: The demand for labor in the Agricultural industry is dynamic, and it becomes especially difficult to find workers during harvest seasons as more people move to cities.
5. Water scarcity: Farmers without access to adequate irrigation water often give up agriculture, leading countries and locations to become dependent on food imports.

With these challenges expected to increase in severity, farmers and the agricultural industry must strive to find alternate solutions. Technology and automation are widely researched for assistance with tasks such as planting, watering, harvesting, etc. Machine learning, robotics, IoT, and protection farming methods have already yielded proven results and are being adopted by countries striving for sustainable development.

Automated Farming - Types and implementation strategy:

Agricultural automation can be deployed at various stages and levels of production, including tillage, planting, crop protection, irrigation, and harvesting. This is the case for most farms from corn fields to automating a vineyard’s crops. One or more of the following strategies can be implemented depending on the farmers' needs or to address a specific agricultural challenge::

• Automated sowing: Automated planting systems use robotics and sensors to plant seeds with high precision, speed, and ensure optimal distance between the plants. This results in better yields and reduced labor costs.
• Automated Irrigation management: Irrigation management uses automation tools such as timers and solenoid controlled valves to optimize plant watering systems. Automated irrigation systems save water consumption, reduce labor costs, and improve crop yield.
• Automated Crop monitoring: Crop monitoring uses drones, sensors, and data analytics to track crop growth, pests, or plant diseases and advise timely chemical treatments. Crop monitoring techniques use image processing and AI-based tools to identify and report diseases in advance.
• Automated Harvesting methods: Automated harvesting systems use robots and conveyors to speed up the process while minimizing labor costs.
• Precision agriculture: A farming management concept based on observing, measuring, and responding to inter and intra-field variability in crops. Precision agriculture aims to optimize inputs' returns by reducing wastage and improving yield using GPS, sensors, and other data-driven technologies.
• Protected agriculture: Also called Climate-controlled agriculture, it is a highly efficient way to develop modern agriculture, using artificial techniques to change climatic factors such as temperature to create environmental conditions suitable for the growth of animals and plants.

Components of an Automated Farming System:

Automation in agricultural farming has traditionally been limited to large-scale operations, but recent technological advancements have made automation more modular, accessible, and affordable for small-scale farmers and even automated home gardening. There are four (4) essential components to every automated farming system: Hardware, software, control systems, and embedded systems. Each of these sections typically consists of a group of smaller parts, working in unison. An automated system integrates the components modularly in order to implement an automation stage or solve an agricultural challenge.

1. Hardware: Selection and installation of hardware components such as solenoid valves, robots, drones, conveyor belts, gateways, image processing lenses, and system integration, calibration, testing, and maintenance lie under the hardware category.
2. Software: ML (machine learning), cloud storage, AI (artificial intelligence) algorithms, application development for remote monitoring, SMS, and E-mail alert configurations.
3. Embedded Systems: Micro-controllers, sensors, communication protocols, and PLC firmware.
4. Control systems: closed loop, open loop system, plant specification, and decision loops

Automation technologies for Agriculture:

The most common automation technologies used in agriculture:

1. Drones: Sensors and cameras mounted on drones to gain critical insights into the health of crops, irrigation and spraying practices, planting operations, soil, and field analysis, plant counting, and yield prediction information.
2. Robotics: Robots and Semi-automatic robots are used to detect weeds and spray pesticides on the affected plants, prevent extensive damage, and reduce pesticide costs and overexposure to chemicals.
3. Automated Irrigation Systems: Automated irrigation systems use weather data to determine when and how much water the crops need. The system then waters the crops accordingly, conserving water and reducing labor costs.
4. Automated Greenhouses or Protected agriculture: Also called "climate-controlled agriculture," automated greenhouses use artificial techniques to change climatic conditions such as temperature and humidity to create an environment suitable for the growth of animals and plants.
5. Crop Monitoring: Integration of Drones, soil, and plant sensors, with data analytics, to track crop growth, pests, or plant diseases and advise the necessary chemical treatments.
6. Precision agriculture: A farming management concept based on observing, measuring, and responding to inter and intra-field variability in crops. Precision agriculture aims to optimize inputs' returns by reducing wastage and improving yield using GPS, sensors, and other data-driven technologies.
7. Livestock Monitoring Systems: Automated systems that track the health and location of livestock using sensors, GPS, and EID (electronic identification). These systems help farmers manage their herds more effectively, reducing labor costs and animal stress.
8. Grain Handling Systems: Automated systems that clean, sort, and store grain using conveyors and image processing systems. These systems can significantly reduce labor costs and improve grain quality.
9. Fertilizer Applicators: Automated systems that apply fertilizer to crops using GPS and variable rate technology. These systems can reduce labor costs and improve fertilizer efficiency.
10. Site-specific crop management (SSCM): Site-specific crop management is the process of making decisions about agricultural inputs on a field-by-field basis. SSCM considers each field's unique soil, weather, and crop conditions.
11. Variable rate technology (VRT): Variable rate technology is the application of inputs at variable rates based on site-specific management. VRT allows farmers to apply different amounts of seed, fertilizer, and pesticides to different areas of their fields.
12. Autonomous vehicles: Autonomous vehicles are vehicles that are capable of sensing their environment and operating without human input. Agricultural autonomous vehicles can perform tasks such as planting, watering, and harvesting crops.

Selection Criteria of Automated Systems for Agriculture:

Often automation technologies are not universal solutions to cater to the needs of all plants, production requirements, and topographic challenges. Apart from a few packaged automated systems, farmers must integrate an automated system based on their specific needs. While selecting an appropriate solution, the following parameters need to be considered:

1. Specific agro needs and objectives of the farmer or farm
2. Crop type
3. The scale of production
4. Climate and weather conditions
5. Soil type
6. Land topography
7. Water availability
8. Pest and disease pressure

Advantages of Automation in Agriculture:

1. Increased efficiency and productivity: Automation can help farmers increase their yields while using fewer resources. Automation technologies can also help farmers reduce their labor costs
2. Improved quality: Automation can help farmers produce higher-quality crops by reducing the need for manual labor. Automation technologies can also help farmers reduce the amount of time their crops spend in the field, improving crop quality
3. Increased safety: Automation can help farmers reduce their exposure to hazardous materials and conditions. Automation technologies can also help farmers reduce the risk of injuries
4. Environmental benefits: Automation can help farmers reduce their use of resources, such as water and fertilizer. Automation technologies can also help farmers reduce their emissions of greenhouse gasses
5. Social benefits: Automation can help farmers improve their working conditions and increase their social and economic opportunities
6. Improved Soil and Water Quality: Automated systems can help improve soil and water quality by reducing the need for chemical inputs

Challenges while Implementing IoT & Automation solutions in Agriculture:

Although automation provides several long-term benefits, farmers must overcome particular operation challenges to implement IoT and automation in agriculture, such as:

1. High Initial Cost: The initial cost of implementing an automated system can be high.
2. Requires skilled labor: Automated systems require skilled labor to operate and maintain complex automated systems
3. Dependence on technology: Automated systems depend on technology and data analytic models, which can sometimes be unreliable and inaccurate.
4. Limited scalability: Automated systems are not always scalable, such as to scale an automated water system installed on a 100-hectare plant will require modifications of pumps, motors, pipelines, etc.
5. Lead to job losses: Automated systems may lead to job losses in the agricultural sector.

Summary and the Future of Automation in Agriculture:

As the world population continues to grow and the demand for food increases, farmers have to adopt robotics, sensors, and artificial intelligence to manage their operations. With the advancement of technologies, automation becomes more affordable and modular, benefitting small-scale farmers. Agricultural automation will play a vital role in meeting this demand while conserving resources and protecting the environment.