Farming is one of the oldest activities in human history. Automation in every industry is a rapidly growing phenomenon in the current world. In that, agriculture automation and precision farming is one of the booming domains. We see vertical farming and greenhouse farming with remote access and its effects on crop growth and health daily. But all of these are built on a plain and stable indoor working environment. What about the mountain vegetation? What about crop monitoring and tech integration in unfavorable terrains? We will dive deep into it.

Light Detection and Ranging (LiDaR)  is a remote sensing method that uses light in the form of a pulsed laser to measure ranges. It is equipped with an aerial robot, mostly a quadcopter which measures the canopy height by using its laser pulses to measure the amount of time taken to receive back the pulse and identify the height and growth of vegetation. They generate high-resolution 3d maps of the region to identify precise heights. Canopy density could be identified by canopy and biomass distribution. Changes in the health and growth of the vegetation could be monitored by a periodic survey (once a week or once in two weeks) of the landscape. 

When hills are bought by planters for less price compared to the plains, then Mapping the terrain before planting helps to capture a detailed 3D Image with complex points, contours, and elevation angles and it is especially useful in the region where it is difficult or dangerous to access by foot or vehicle. such as cliffs, dense, impassable forests, or rugged mountains. With drones, proper flight planning could be done beforehand to utilize the maximum potential of the terrain. Unmonitored terrain may contain wildlife which might be harmful for the upcoming plantation and the humans in the region. Hence those locations could be avoided from the planting region for estates above 50 acres. LiDAR technology can help minimize the amount of disturbance to sensitive ecosystems.

The drones play an integral role in spraying pesticides. Drones made for both the private and government sectors and by private entities like CAMPCO (Central Arecanut and Cocoa Marketing and Processing Co-operative Limited) are being marketed by Fuselage Innovations from Maker Village, Kerala. The Israeli drip irrigation group is the world leader in providing innovative drip irrigation by inculcating Artificial Intelligence and Machine Learning to the irrigation systems by controlling the water flow based on crops mapped on the maps and helps save water by 80% by not spraying on the locations where plants are not there and also by controlling the mist flow for each crop.

From the most basic job of getting the land ready to plant to the process of harvesting and clearing, this new technology could be applied. And day by day companies like ONDO-Smart Farming Solutions and Appharvest innovate new methods to increase efficiency.

Productivity zones are created on very large-scale estates based on the soil of one sector. which helps to plant different varieties of the same plant to increase the crop yield. these are done with ground staff collecting soil samples by comparing them with historical data and combining it with satellite maps to form a clear idea regarding crop selection.

The first step of clearing the land is said in the above section. The land has to be surveyed to remove potential threats to proceed to the second phase which is seed selection, by using ML (Machine Learning) image recognition algorithms to identify non-germinating seeds based on the weight, color, and in-depth image data reports of the seeds. this is to reduce the wastage of land and just focus on producing crops of export quality. this method is widely used in orchard farms in the United States and Switzerland, it helps to improve efficiency by more than 25 percent.

DL Model to monitor plant health, Source: pyimageresearch

Automation may be linked with increased unemployment and job displacement for unskilled laborers; not only can this have negative implications for inclusiveness, but it can distort perceptions about its benefits. Policies can play a central role in mitigating or avoiding any negative impacts. 

 The deployment of small machinery has enabled small-scale producers to automate many agricultural operations. Institutional mechanisms, such as shared service provision and cooperative ownership facilitated by digital technologies, have supported the adoption of automation technologies. (Chapter 3, Food Agriculture Organization of the United Nations)

Women often have less access to automation technologies – partly because their plots are smaller and more fragmented and they have less access to markets, credit, and extension. Policies, legislation, and investments that address these disadvantages can help increase their access to automation. (Chapter 4, FAOUN)

Automated farming can make agriculture more profitable while also making farming sustainable. By implementing precision farming techniques, farmers can selectively reduce their environmental footprint by applying pesticides and fertilizers, decreasing the chemicals in the surrounding soil and waterways. 

Labor is over 50% of the cost of growing a farm, and 55% of farmers say labor shortages impact them. Because of this, 31% of farmers are moving to less laborious crops. However, there is a vast potential for harvest machine learning. Routine tasks can be automated with robotics technology, reducing labor costs in the agriculture industry. High costs to adopt robotic technologies can be a considerable barrier to entry for farmers, especially in developing countries; Technical issues and equipment breakdown can also present high fees to fix such specialized equipment. 

According to a report from McKinsey and Company's agriculture division, Recently Automated vineyards in the United States were able to create an EBITDA (Earning Before Interest Tax Depreciation and Amortization) Margin savings of 35% from their total expenditure. when it is tracked down to pennies the savings are like ~$800 per acre from Automated Pruning, ~$300 per acre by automated spraying, ~$200 per acre from automated weeding and moving, and ~$ 700 per acre from automated harvesting. when taking care of the scale of these farms which are above 1000 acres, the margin growth is phenomenal. Meanwhile, these values might reduce by ~10% to 15% when applied to the hilly terrains because of the difference in the requirements of machines and the time consumed.  

Embracing automation in challenging terrains is not just a luxury but a necessity for the future of plantations. The need for efficiency in agriculture, especially in tough landscapes, cannot be overstated. Automation offers a solution to the many hurdles faced by farmers in unfavorable terrains, from difficult topography to extreme weather conditions. By introducing smart technologies and automated systems, we not only alleviate the physical burden on farmers but also enhance productivity. The precision and accuracy of automated machinery ensure that resources like water and fertilizers are used optimally, reducing waste and promoting sustainability.

Furthermore, in areas where manual labor might be scarce or expensive, automation becomes a cost-effective and reliable alternative. It opens up new possibilities for increased yields, making agriculture more economically viable for farmers. In the face of climate change and the growing global population, the importance of efficient and sustainable agriculture cannot be ignored. As we move forward, we must embrace technological advancements to cultivate a resilient and thriving future for our plantations and the communities that depend on them.

Nelson Ferreira, David Fiocco, Vasanth Ganesan, Maria Garcia de la Serrana Lozano, Ana Luiza Mokodsi, Otto Gryschek, McKinsey and Company Global Farmers Insights (2022)

Rockrobotics, LiDAR Measuring Vegetation Health in the Forestry Industry (2022)

The Hindu Beareu, (2024) AI, machine learning, and automation present a new face of the plantation sector.

Elhassan Mohammed Elhassan Ahmed, Khalid Hamid Bilal Abdalla, Ibrahim Khider Eltahir, IEEE  (2020) Farm automation based on Iot

World Economic Forum, (2023) Rise of Autonomous Farms

Ondo, (2022) Sustainable farming in a profitable way

Dough Fitch, (2022) Digitizing and Automating Fruit Orchards to improve results.

James Vincent, (2018) The robotic farm of the future isn’t what you’d expect

Vasyl Cherlinka, Scientist at EOS Data Analytics, (2020) Crop Yield Increase With Precision Technologies

GEOFFREY LING & BLAKE BEXTINE, (2017) Precision Farming Increases Crop Yields

Paras, IIT Kanpur, (2019) DIC’s Terrace Farming Robot for Hilly Areas. 

Puneet Mangla, (2022) Computer Vision and Deep Learning for Agriculture

Acharya, S.S. 2001. Domestic Agricultural Marketing Policies, Incentives and Integration. In S.S. Acharya and D.P. Chaudhry. Indian Agricultural Policy at the Crossroads: Priorities and Agenda. Rawat Publications, Jaipur and New Delhi.

Agarwal, B. 1994. A Field of One’s Own. Cambridge University Press. Cambridge, 572 pp.

POLICIES TO ENSURE AN INCLUSIVE AGRICULTURAL AUTOMATION PROCESS THAT WORKS FOR ALL