Engineers and scientists who developed an electronic nose for wine testing and a groundbreaking wireless charging system for electric vehicles are boosting their abilities with MATLAB, an engineering platform from mathematical computing developer MathWorks.
The platform empowers engineers and scientists to successfully apply AI, automation, data analytics and predictive maintenance technologies across their project workflows.
MathWorks developed its MATLAB and Simulink platforms so engineers and scientists could collaborate better on AI datasets, integrate community AI models, rapidly iterate and test AI models system-wide. Recognised for its innovative approach, MathWorks is a 2021 Leader in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms and the leader for completeness of vision within the quadrant.
“We’ve been steadily building out more and more apps for non-technical engineers, or engineers who may not have the programming capabilities to develop new systems. With our tools and apps, you can now develop an AI or machine learning application with almost no coding required,” said Stephane Marouani, Country Manager Australia and New Zealand, MathWorks.
Associate Professor Sigfredo Fuentes is a plant physiologist at the University of Melbourne. He uses MathWorks across Vineyard of the Future, an international consortium of scientists that he leads to explore new technologies for the wine industry. Each project is quite varied and pushes the boundaries of available technologies, bringing components together to deliver a greater impact.
Using advanced GPS monitoring and motion detection, his team trains sniffer dogs to hunt down a damaging and hard-to-find vineyard pest called phylloxera. And when the dogs’ noses weren’t accurate enough to test aroma profiles, his team went on to develop an e-nose. Combined with a robotic pouring arm, camera sensors and the e-nose, they can detect aroma profiles with 97 per cent accuracy across various wines and beers.
During the 2019-20 Bushfires, Fuentes and his team developed computer vision algorithms that use heat signatures to detect smoke contamination with vineyard canopies. With 96 per cent accuracy, it enabled winemakers to make more informed decisions about their crops. MATLAB helped his team bring together algorithms and information from across various toolboxes to develop prototypes for each of these innovative projects.
“We’re excited about the role we play in helping engineers and scientists like Professor Fuentes to support them with tools like MATLAB and Simulink. We also have a really engaged global community of engineers and scientists who actively share knowledge and ideas across our forums. We love seeing the incredible ideas and projects that are developed by people using our tools,” added Marouani.
MATLAB also helps speed up the time it takes for designs to be realised. The McLaren Speedtail Hyper-GT is the British auto manufacturer’s fastest road car ever, with a prototype hitting 403 km/h during testing. McLaren partnered with Lumen Freedom so the Speedtail could become the first vehicle in the world to incorporate their Wireless Electric Vehicle Charging (WEVC) system. Its design team turned to MATLAB and Simulink when they hit an unexpected roadblock during development.
With Speedtail and the WEVC system, the electric vehicle has a communication controller that manages communication between the vehicle and the ground assembly. The controller sends crucial messages to the vehicle charging pad and the vehicle’s internal battery management system. This communication had to shift from a hardwired controller to a Wi-Fi-based one which required remodeling the machine. Developers were able to complete the changes in less than a day using MATLAB and Simulink.
In Australia, there is an increase in projects that involve electrification, strong modeling simulation, predictive maintenance or breaking new boundaries across the mining and agribusiness sectors. Many of these projects demand new sets of skills for engineers to develop. With MATLAB, there are toolboxes already available from deep learning to pure AI, automated driving, radar development and more that all come with support to integrate these modules together.
To hear more innovative projects being developed with MATLAB, register to attend the virtual Asia-Pacific MATLAB Expo, 4-5 May 2021