Bridging the Fragmented Landscape of Agricultural Technologies

November 23, 2023

By Alon Ascher

Alon Ascher, Chief Business Officer of Bluewhite, leveraged over 15 years of management experience in autonomous, robotics, and software technologies at the Israeli Air Force and startups. Alon brings intensive expertise in leading business, GTM, operation, and product strategy. Alon is leading Bluewhite’s business teams – business development, sales, marketing, and customer success. Alon holds an ME in system engineering from Technion (Israel) and a BA in Information Systems from BGU (Israel).  Prior to Bluewhite, Alon founded an AI software startup, served as a technology consultant to Israel’s minister of transport, and served 13 years in the Israeli Air Force, as an Apache pilot and R&D program manager.

Modern agriculture is no stranger to innovation. For the last two decades, the agricultural market has seen a technological revolution, poised to redefine the way we produce and consume food. From precision farming to automated irrigation systems, the industry has witnessed a surge in advanced technologies designed to enhance productivity and sustainability. Yet, this promising landscape is marred by fragmentation – a phenomenon where different technological solutions exist in isolation, without seamless integration or coordination, limiting the innovation’s full potential. I see the urging need for connectivity and collaboration among different solutions, robotics, and data platforms, especially in the transformative role autonomous robots have in high-value crops

So, why do we see this fragmentation? First, the agricultural technology market is complex and diverse, supporting different crops, geographies, and needs – requiring vendors to offer specialized solutions. While this diversity fuels innovation, it also leads to disjointed systems that struggle to communicate effectively with each other. Building a solution that is rolled out as specific niches, such as precision planting or yield monitoring for a specific crop, hinders the creation of a comprehensive and integrated agricultural system. In addition, the absence of standardized protocols and interfaces prevents interoperability between technologies. As a result, data collected by one system may remain trapped, unable to contribute to a holistic understanding of the farming ecosystem.

Now, why this connectively is impotent? A connected agricultural ecosystem allows for real-time data sharing between various technologies. This data-driven approach empowers farmers to make better-informed decisions, optimizing resource allocation and crop management. The collaboration between robotics and data analytics can lead to smarter resource utilization at lower ‘insight cost’. If one service implementation can cover most of the cost to generate the other service – we get expansion returns. For example, an autonomous tractor mowing the field can detect irrigation leaks while executing its job. Interconnected systems can automatically adjust irrigation levels based on this information, reducing water waste and cost – without the need to send specific irrigation teams across the farm. Although these are two different technologies serving different purposes, the integration offers higher efficiency and better holistic management of the farm.

I see autonomous robots as a transformative opportunity for 21st-century farming. While autonomous robots spraying, mowing, discing, and more through orchards and vineyards, dozens of times a year, they are collecting intricate data about plant health, growth patterns, and environmental conditions. Leveraging their onboard sensors, computing, and communication, and even utilizing them as an LTE relay to additional farm sensors, make datasets far more accessible. These new and unique datasets provide invaluable insights that were previously inaccessible. By pinpointing precise areas requiring attention, resources are allocated efficiently, reducing waste and optimizing production. The availability of plant-based data opens doors to new innovative services. Machine learning algorithms can analyze the data to predict disease outbreaks, optimize pruning techniques, and even suggest personalized care strategies for each plant. As farms evolve from offline business to online data-driven ones, they face the huge potential for innovation as we see in other ‘traditional’ markets like logistics, construction, or mobility.  Besides improving agronomist, yield and operation efficiency, new insurances, equipment lease and service programs, employee training, asset management, crop marketing, and farm logistics, can also transform end to end.

The fragmented state of agricultural technologies presents both challenges and opportunities. By recognizing the imperatives of connectivity and collaboration, and by embracing the transformative potential of autonomous robots, we can transcend these challenges and pave the way for a unified and technologically empowered agricultural landscape. The fusion of different vendors, robotics, and data, along with the game-changing role of autonomous robots, holds the promise of revolutionizing how we produce food. It ensures sustainability, resource efficiency, increased yields, and the birth of innovative, data-driven services. Most importantly, it will improve growers’ peace of mind and bottom line.