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ListenField Enables Farmers To Harvest The Benefits Of AI And Machine Learning

  • aster.cloud
  • September 7, 2023
  • 4 minute read

When I was growing up in Thailand, I witnessed the challenges facing farmers including rising food demand, shortage of labor, and uneven crop yields caused by climate change. As a result, many smallholder farmers found themselves trapped in a vicious circle, unable to reduce food insecurity due to low yields, but lacking the resources to invest for a more profitable future.

I was determined to make a difference. After earning my master’s degree in Information Management I joined a research project with the University of Tokyo where we used sensors to monitor spinach fields in Thailand. The results of this early experiment in precision farming were impressive. We proved that it was possible to grow organic crops with minimal use of fertilizers, while consumers benefited from higher quality spinach grown in Thailand.  


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This inspired me to found ListenField in 2017. Our mission is to transform farm management by collecting data from multiple sources, including field sensors, soil scanning, weather data, seasonal forecasts, and satellite imagery. By modeling this data, we provide farmers with insights that enable them to optimize production ‘from soil to harvest’.

A bumper crop of farming data

Artificial intelligence and machine learning play a central role in our prediction platform, combining crop health monitoring, growth prediction, and soil nutrition analysis. Farmers can apply real-time insights to their schedule from our FarmAI Mobile App, while our FarmAI Dashboard enables agri-food businesses to collaborate with agronomists and farmers so that all parties benefit from higher profit margins and more sustainable growing strategies.

Another important feature of our business model is AgroAPI, which makes our analytics available to third parties. Clients can embed deep analytics in their applications, including crop growth prediction and remote sensing analysis, without needing to develop complicated algorithms and data pipelines by themselves.

Read More  Microsoft And Oracle Expand Partnership To Deliver Oracle Database Services On Oracle Cloud Infrastructure In Microsoft Azure

We are also excited about our research into genomic prediction in collaboration with the Japanese government and several research companies. Using our Data-Driven Breeding Platform, breeders and seed companies can upload their genomic data and gain practical insights that help accelerate the reproduction of high-quality seeds and plants.

Today, more than 30,000 farmers use our technology especially in Vietnam and Thailand where it is used to improve rice, cassava, and sugar cane yields. The technology is also being rolled out for orange and mango farmers enabling them to monitor individual trees and adjust irrigation to improve the sweetness of the fruit at harvest time.

Responding fast to changing conditions

We were using another cloud provider to run our business, but one of the ListenField team members drew our attention to Google Cloud. As well as the technology, we were also attracted by the Google for Startups Cloud Program which provides us with Google Cloud credits that cover our first and second years of Google Cloud usage. We also met our Account Representative, who provides us with training, business and tech support, and Google-wide discounts. It’s great to have a point of contact that can help us on our startup journey and make the most of Google’s resources.

By reducing the pressure on our finances and human resources, we were able to experiment and adapt in response to early experiments. This flexibility also enabled us to demonstrate a compelling business case to new and existing investors.

Our Google Cloud Platform Partner, Navagis, gave us additional momentum thanks to their expertise in mapping and geospatial data. They also played a crucial role in the integration of Google Earth Engine, which we use to map agricultural areas.

Read More  9 Ways To Use Open Source Every Day

We also use Firebase for application development and Google Workspace for team collaboration. Colab and Vertex AI enable us to build, deploy, and scale our machine learning models quickly, ensuring that we remain competitive and attractive to new customers.

Giving female entrepreneurs the opportunity to flourish

Both the Google Cloud team and our colleagues at Navagis helped us to navigate the challenges many early-stage startups face. My background is in science and academia, so I appreciated the business mindset offered by both organizations to help us continue to grow and scale.

Being a female entrepreneur leading a startup can also be tough, but Google Cloud and Navagis helped me to build a strong network, access funding, and make my voice heard. Today, ListenField has several female executives, while 50% of our researchers and many of the farmers on our platform are women.  

Above all, Google Cloud helps us to power an agriculture revolution in south-east Asia. Smallholder farmers can transition from analog to digital farming, improving their yields and reducing waste. The benefits to the economy are also significant including greater food security and reducing the use of industrial fertilizers that generate potent greenhouse gasses.

And that’s just the beginning of what we can do. Our next milestone is to reach 50,000 farmers and cut one million tonnes of greenhouse gas emissions. It sounds ambitious, but with the Google Cloud and Navagis teams behind us, I’m confident that we will reach these targets.

ListenField team members

If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.

By: Rassarin Chinnachodteeranun (Founder and CEO, ListenField)
Originally published at Google Cloud Blog

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Related Topics
  • Agriculture
  • AI
  • Artificial Intelligence
  • Farming
  • Google Cloud
  • ListenField
  • Machine Learning
  • ML
  • Startups
  • Thailand
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