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Investing in drones for the future, developed in the field

Mike Ritter, chief executive at private equity-backed US agri-drone sensor and analytics developer SlantRange, explains why investors should focus on drone technology specifically created for the sector.

Mike Ritter, chief executive at private equity-backed US agri-drone sensor and analytics developer SlantRange, explains why investors should focus on drone technology specifically created for the sector.

Commercial drones have a huge potential, with market value expected to reach $127 billion by 2020, according to PwC. But no sector holds as much potential as agriculture.

The Association for Unmanned Vehicle Systems International says that precision agriculture could account for 80 percent of commercial drone use by 2035. However, current technology cannot capture most of that market value.

The capability shortfall is due in part to where investment has been focused. Many agricultural drones are still too closely based on tech designed for other areas. Most investment has been directed at flight systems, drone service models and cloud computing architectures for horizontal business platforms.

Agricultural production is complex, and has extremely diverse information needs across the industry. Nebraskan corn producers ask for accurate emergent plant density measures. Florida citrus producers ask for early bacterial infection detection. California forage producers ask about a particular noxious weed.

Low-altitude drones could deliver these specific types of information cost-effectively, yet most of today’s systems deliver information on a one-size-fits-all basis. Many offer contrast-enhanced field pictures, borrowing a 1970s-era satellite imaging technique originally intended to merely detect growing vegetation.

Our first backers were Nebraskan corn and soybean growers with strong opinions on the information they needed. Early on, they described the time and cost of assessing their number of plants per acre, and weed coverage shortly after planting, showing us how scouts manually counted plants in the field. They based replanting and herbicide treatment decisions on the research. We soon commercialised an automated process combining spectral imaging with computer vision and artificial intelligence to do the work using drones. Efficient collection of specific data needs more investment in mission-critical remote sensing and analytics technologies.

The actual value of drone data to agriculture, and critically, the manner in which it is captured and converted into actionable information, has also been largely overlooked.

The cloud-based data-processing and software-service models that have streamlined many industries are ill-equipped to handle the enormous volume of raw data agricultural drones generate. Broadband network access does not exist over much of the world’s agricultural land. Even where it does, it is not designed for massive data-upload volumes. If data can’t reach the server, cloud processing is not a viable option, with farmers unable to access analytics. Distributed processing architectures which analyse data at the point of collection are currently the only scalable option.

We’re filling a critical market need in this respect to help farmers. We have developed new technologies that dramatically reduce the volume of raw data and time required to collect and process it onsite, without the need for network connectivity or high-end computing infrastructure. The technology makes advanced sensors and analytics technologies accessible to farmers in developing regions where it could have the largest impact.

Drones hold immense potential value for agriculture and investors. Its full value will be realised when more applicable information can be delivered to farmers and agronomists internationally, in real-time. To get there though, companies must get out of the office and into the fields, where they can work closely with agronomists to identify specific information needs and understand agronomist workflows. Simply transplanting technology and business models from dissimilar applications is unlikely to work. It’s time to invest in drone technology engineered specifically for agriculture.