Open Source Summit Japan & Automotive Linux Summit 2020

Giant Hogweed is a highly toxic plant originating in the Western Caucasus. It has spread across Central and Western Europe and there are sightings of Giant Hogweed reported from North America, too. Landowners are obliged to eradicate it, due to its toxicity and invasive nature in Europe. However, it is difficult for landowners to find and remove Giant Hogweed across large areas of land since it is a very cumbersome manual process. To automate the process of detecting the Giant Hogweed by exploiting technologies like drones and image recognition/detection using Machine Learning is an effective way to address this problem. In this presentation, we show you how we designed the architecture towards the Petabyte scale, how we took advantage of both of Big Data and Machine / Deep Learning technologies and lessons learned through this project. For example, we integrated a drone, Apache Hadoop, Apache Spark and TensorFlow to achieve the usability, flexibility and scalability for both of data engineers and data analysts. We talk about why this integration was needed for us, technical challenges from the viewpoint of enterprises and tips to leverage the above open source software.