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Presentation: Internet of Tomatoes: Building a Scalable Cloud Architecture

Track: Streaming Data Architectures

Location: Whittle, 3rd flr.

Duration: 10:35am - 11:25am

Day of week: Monday

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What You’ll Learn

  1. Hear about 30Mhz’s data platform and how they collect data from a large number of agricultural sensors.
  2. Find out 10 architectural patterns that help build a platform for scale.


Five years ago we started on a journey of building a website monitoring tool. Little did I know that this would land up morphing into a full IoT based agriculture platform. Discussing if tomatoes need dark hours to sleep was not the type of question I had anticipated having to answer. But don't underestimate how you can innovate the agriculture world with your technology. At 30MHz we're building a data platform for the agriculture sector. It provides full insight into the climatic conditions of horticultural and agricultural produce for all stakeholders in the sector. This includes ingesting all kinds of data sources and analysing the information interactively - enabling the continuous improvement of the production process for crops, plants, seeds, and bulbs.   In this talk I'll tell the story of our platform and how we ended up helping growers in 30 countries, deploying 3.5K sensors and process data at 4K events per minute. I'll share our architecture, how it grew, the challenges, and how we are continuing to transform it - for example - to learn how to grow the best tomatoes!   Key takeaways:  

  • Gain insight into a concrete solution for gathering, storing and accessing big amounts of real-time time-based data.
  • Understand some of the problems that you could encounter building such a platform.
  • Get inspiration for embarking on projects related to IoT, (big) data collection or even getting into the agriculture industry.

What is the work you're doing today?


I am the CTO of 30MHz, we're an agriculture platform company. Our users are farmers and we try to gather all of the data from different systems onto one platform to enable them to work with it, to visualize it, learn, advise, communicate about it. One important part of our platform is sensing the data. From the beginning, we have been working with sensors that we connect to the platform. We collect data every minute. So sensor data is a big part of it. And this is data which is coming continuously, every minute for every sensor. These can be sensors for temperature, air humidity, soil humidity, CO2, these kinds of things.

Another nice thing to mention that we are working on is the Autonomous Greenhouse Project. We are using machine learning techniques to make an application which advises the grower on the best climate conditions for their crops and even to automate the control of their climate in a greenhouse. We are participating in a competition called Autonomous Greenhouse with the challenge to grow cherry tomatoes for six months remotely using artificial intelligence or data science techniques.


Do you also go into the fields and put down sensors?


We integrate sensors and produce them to connect to our platform. They are wireless. As part of our offer, we provide wireless sensors which you can choose and locate in your greenhouse or even outside. We don't build the sensors ourselves, but we select them and integrate them to our platform by making them wireless and optimizing them to run on battery with very low power usage.


When you say wireless, are we talking about 3G?


I am not planning to talk much about this, but we use a proprietary wireless protocol called XBee. It's pretty efficient and allows us to send data very frequently. From all the options that we have tried, this is the one which works best.


What kinds of technology do you use internally for gathering all this streaming data? Kafka?


We don't use Kafka at the moment. It's something we consider. We started building our platform seven years ago. Our architecture, running on AWS, is based into different components, each with a very specific function. Each of these components is resilient in itself, and they communicate with each other using queues, SQS.

This is one of the topics I want to touch on. I want to talk about the evolution of the architecture and how we started, because the original platform was built for web monitoring, and then we incorporated sensors, and later we decided to totally focus on agriculture. I'll discuss the impact of these changes and how by having a robust architecture you can adapt it without too much pain. Along the way, we have found specific issues when trying to scale or to change and in each case, we solved them by replacing specific components, a bit like playing with Legos.


What are the takeaways from your talk?


I'm going to give 10 architectural patterns to build software for scale. Be ready to scale two or three times the current load is one of the things that I would advise. Monitor everything because then you know which parts you have to re-architect. If you architect for scale, your platform can adapt to new functionality.

Speaker: Flavia Paganelli

CTO and Founder @30Mhz

Flavia is co-founder and CTO of 30MHz, a data platform for agriculture with a mission to grow food more sustainably and efficiently. At 30MHz, the challenges range from managing a fleet of thousands of devices to making beautiful visualizations for data, and let's not forget the terabytes of data that need to be always available and quickly accessible.

Before 30MHz, Flavia founded 9Apps, a cloud boutique which helped startups scaling their Amazon Web Services infrastructure. ​She gathered the experience with AWS in three books published by O’Reilly: Programming Amazon EC2​,  ​Elastic Beanstalk, and​ Resilience and Reliability with AWS,​ which she co-authored.  

Flavia also worked at TomTom, where she developed their web route planner, and then at Layar to build their mobile Augmented Reality app.      

With a background in Computer Science, Flavia has been building software in diverse industries, languages and teams for more than half her life, and she is not planning to stop.

Find Flavia Paganelli at

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