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Telesense, an agritech startup based in Silicon Valley, is using IoT devices to solve bulk grain storage challenges farmers face. By embedding smart sensors in silos and trucks, the company provides farmers with real-time data on temperature, humidity and fumigant gases, three factors responsible for grain spoilage and resulting losses. By using digital technology, the startup hopes to significantly cut down overall spoilage rates and in the process boost the amount of food that makes it to market as well as farmers’ profits.

With the world population projected to reach 11.2 billion by the year 2100, Agricultural Technology or AgriTech is seen as one possible solution to sustaining food production rates over the next century. To highlight digital transformation innovations currently reshaping the agricultural sector, we cover six examples that can not only increase food production but provide better resource utilization and environmental stewardship capabilities to farmers.

1. Smart Fields

Fields are the backbone of the agricultural industry. As a key resource, management, utilization, and optimization hold the potential to increase per-acre production. One digital technology that can transform this is smart sensors or IoT devices. By embedding smart sensors in fields that report on the soil moisture and nutrient content, visualize, analyze and categorize weeds and other impediments to productive yields, farmers can gain deep insights on how each acre of land is performing.

Another growth area that smart fields can impact is the crop farming cycle of planting, weeding, and harvesting. As crops mature, embedded smart sensors can report on how each batch of crops is performing by reporting metrics like sap flow, crucial data for understanding how crops are performing. Further, smart fields can generate data that can be analyzed to determine per-acre seed selection and placement metrics, an aspect that most farmers currently estimate using non-dynamic historical data.

2. Smart Machinery

John Deere is at the forefront of digital transformation in the farming machinery sector. While in the past farm machinery was sold as a product, today, the company is pioneering Machinery-as-a-Service by selling smart equipment connected to the cloud. Farmers purchasing the equipment can utilize smart could applications to not only run the machinery but to also collect and analyze data related to performance, run rates, maintenance requirements, and others.

Unlocked potential of smart machinery can increase farm throughput, lower downtime and reduce overall spend arising from operating machinery within redundant parameters. Further, smart machinery will remove focus on machinery and retrain it on processes. In this way, farmers will not be looking at individual pieces of machinery, but through data, will be able to see the entire farm, working as a networked system, an advancement that could help isolate inefficiencies and bottlenecks.

3. Smart Foods

According to the CDC, 48 million Americans get food poisoning every year with 128,000 of these cases resulting in hospitalization. Of all foods consumed, fresh vegetables account for close to a quarter of all food poisoning cases. One major challenge with combating food poisoning is tracking the source of produce. In the recent romaine lettuce E.coli outbreak in the United States, the vegetables were tracked to a region, but any granular tracking beyond this was impossible.

One example of how this challenge can be solved through digital technology is the collaboration between Walmart and IBM to put all the supermarket chain’s lettuce on the blockchain. By creating an immutable ledger that tracks the more than 100 touch points between farm and shelf, Walmart hopes to track the source of any bad batch of lettuce, not in days, but in mere seconds. This will allow for the selective destruction of bad batches of lettuce, compared to what they had to do during the E.coli breakout, which was indiscriminately clear all lettuce off their shelves. By tagging all foods in a similar manner, it would be possible for food sellers, government agencies like the CDC and even consumers to track food from farm to fork.

Another application of digital tools in food management would be in the reduction of wastage. With an estimated 150,000 tons of food wasted each day in the United States alone, it is possible, through smart sensors and predictive analytics, to scale up and scale down food supply to match real-time demand and thus reduce wastage.

4. Drones

Unmanned Aerial Vehicles (UAVs) represent a gigantic opportunity for farmers. Current technologies employ small aircraft and other methods to monitor crops, deploy pesticides and perform other operations at scale. However, these technologies are tied to labor and therefore suffer from scaling challenges. With UAVs, farmers can track and manage large tracts of farmland with zero field labor. Controlled from a central hub, the drones would be able to operate nonstop and with little human supervision.

An area that is rapidly advancing is drones equipped with smart sensors and precision targeting. These drones perform field and soil analysis by generating 3D maps, plant by shooting seeds into the soil, apply precise fertilizer, monitor crops, irrigate and perform health assessments. PwC notes in an article published in the MIT Technology Review that the future of drones may involve swarms of autonomous or semi-autonomous UAVs that tackle not only routine farming tasks but also tackle bigger climate and environment-related challenges.

5. Robots

Oz Weeding Robot is a small semi-autonomous robot that crawls through planting rows removing weeds and aerating the soil. The robot, built by Naio Technologies, can “see” the crop rows, navigating from one row to the next with no human intervention. Blue River Technology, an AgriTech startup recently acquired by John Deere, is pioneering a “see and spray” technology that uses smart optic sensors to target each plant for weeding and spraying.

Such technologies are targeting areas in farming that are currently labor intensive. With such digital transformation innovations, farms can gain farm process efficiencies tied to labor savings. One challenge farmers will face when it comes to full-on robot deployment is the delicate balance they must maintain between pure profit and socio-economic factors like job losses. However, according to a Deloitte paper on the future of work, automation may not be all doom and gloom for the labor market. The paper noted that though 800,000 jobs have been lost to date due to automation, close to 3.5 million jobs have been created in the fields of automation, Ai, and others.

6. Ai and Predictive Analytics

Consider a situation where a farmer, about to start their day, holds a briefing with an “Alexa for farming,” instructing the Ai to perform several tasks. Within the same context, the farming Ai would also report to the farmer analyzed and simplified data related to weather stations, weather forecasts, plant sensors, autonomous farm machinery, and drones. All this data, flowing in by the terabyte, would be filtered by the Ai to present meaningful and actionable insights to the farmer.

As farming shifts from utilizing historical data to leveraging predictive analytics, Ai will play an increasingly pivotal role in not only processing this data but also actioning it. For instance, an AI spotting a patch of weeds would not need to notify the farm manager. Instead, it would activate and deploy either a drone or robot to the site to eliminate the weeds. This type of elastic autonomous Ai represents a disruptive opportunity for farmers interested in pioneering the autonomous farms of the future.


A silent agrarian revolution is underway. Unlike the previous revolution that came with tractors and other highly-visible tools, the current revolution is occurring at a software-driven sublayer, where the agricultural platforms and ecosystems of the future are currently in development. Farmers looking to increasing per-acre output must look to digital transformation to drive down the cost of labor, increase the overall precision of farming processes, and distill insights that will help predict how best to increase yields. Doing this will not only ensure the survival of farming enterprises but retool such enterprises to feed a rapidly changing planet.


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