Although precision agriculture is an important tool for feeding a growing planet while minimizing environmental damage, the motivation for farmers is less altruistic. According to Eduardo Barros, Accenture’s Global Products Agri-business Lead, data-driven decisions about irrigation, fertilization and harvesting can increase corn farm profitability by $5 to $100 per acre. Barros adds that a 6-month pilot study found precision agriculture improved overall crop productivity by 15%. It seems like a no-brainer for farmers if not for the nasty implementation details: new sensors and equipment for granular data measurement, data collection, integration with third-party data sources like weather models and satellite imagery, and number-crunching data analysis to produce recommendations. While not insurmountable hurdles for big corporate farms, the technology requirements and expertise are beyond the reach of smaller farmers, particularly in developing countries. Enter cloud services: the same technology equalizer that allows two-person startups to develop software using hundreds of servers can deliver sophisticated agricultural analytics to the family farm.
By combining aspects of IoT and big data, precision agriculture has a lot in common with burgeoning analytics applications in many other industries. The need for prodigious data collection, from many sources, associated storage and computational horsepower makes it a great fit for cloud services. Not only do shared services broaden the available market for precision agriculture, but the cloud enables agricultural crowdsourcing, by aggregating data from a wide variety of smaller operations to improve prediction models.
The field has already attracted the attention of big companies like IBM, which has researchers working on agricultural weather forecasts, models and simulations to improve farm decisions, and Accenture, along with a host of startups as profiled in this Forbes column. Yet farming is a hands-on activity and many of the measurements that feed precision agriculture models require instruments and implementation expertise that small farmers don’t possess. That’s why Accenture has segmented its offering into two services: one for large agribusiness with the necessary equipment and sophistication to use a pure SaaS product and another for small operations, particularly in developing countries, that rely on an agricultural version of the channel: agro-service agents that work directly with individual farmers. In this case, Accenture’s software provides decision support for companies that already sell a range of agricultural products like seeds, fertilizer and pesticides. Barros says Accenture’s software can even integrate with ERP and HR systems to automate orders and schedule field workers.
An important similarity between precision agriculture and broader trends in business software is the use of location services. Of course, farms are inherently tied to location, making agriculture a natural early adopter of GPS services, such as fertilizer spreaders that can apply different amounts according to location, and autonomous vehicles. Drones represent the next frontier for data collection (field imagery) accuracy and frequency and perhaps product application (fertilizer, herbicides). Just like an array of equipment sensors in a power plant or aircraft, all of this fine-grained location data can feed analytic models, however as with industrial IoT, the amount of data can be overwhelming, reinforcing the case for cloud deployment.
Although Barros didn’t discuss Accenture’s implementation specifics, given the amount of data collected and the episodic nature of model calculations, precision agriculture software is a great fit for IaaS platforms like AWS or Google Cloud. With a variety of services like NoSQL plus Hadoop data analysis and HPC compute grids, including support for GPU instances by AWS for parallelized number crunching, cloud infrastructure is an ideal way to develop precision agriculture software and deliver packaged services to customers like small farmers with few IT investments and little expertise.
Although relatively small, one estimate shows the precision agriculture market growing at over 13% per year hitting $3.7 billion by 2018, with the rate in emerging markets expected to exceed 25%. According to an investment bank report on precision agriculture, “The entire industry is realizing that a key value driver in the development of precision agriculture is data — collecting it, analyzing it, and using it.” Although data collection will remain a local problem, shared cloud services can accelerate the analysis and lower the barriers to farmers needing actionable intelligence. Precision agriculture will be an interesting field to monitor for both technological advancements and investment opportunities.
This article was published on Forbes in the section on Tech on August 25, 2o15 and was retrieved on September 4, 2015 and reposted for educational and information purposes.