25th October, London
On 25th October some of the Thrive team attended Hardware Pioneers Max 2022. It was great to be back at an industry event and explore the UK’s leading trade show driving the acceleration of success for engineers, product managers, and technical leaders who develop B2B and B2C IoT devices and wearables. The day consisted of a vast number of exhibitors, suppliers, and industry pioneers sharing their insight. We attended various talks from companies and discovered hardware innovations that can be applied to IoT to speed up development processes.
Some key highlights from the talks we attended were by Amir Sherman, Global Director from Edge Impulse exploring “How to supercharge your edge ML application” and discussing the benefits of using MCU, MPU, or neural network engine solutions. Applying edge processes can enhance wearable devices by leveraging sensor data to develop a richer end-user interaction and enhance user-privacy protection. This is a topic close to our heart as we’ve discussed how 5G and edge processes are crucial to transforming wearable tech for the better. Read our findings here
Sherman went on to discuss the growing demand for edge ML and what factors can help in choosing the right hardware. With so many hardware choices available it can be difficult to find the most suitable core for your application. By applying Edge Impulse to the process, embedded engineers and domain experts can find the most suitable core for their design by being able to automate the process of gathering data and anomaly detection. Another benefit is that it enables users to build and test machine learning applications and can easily integrate with tools usually used by embedded engineers as it supports most technologies and solutions in the industry.
We also attended a presentation by Andrew Anderson, Field Applications Engineering Manager, from Micron as he discussed “Memory and Storage innovations: Accelerating intelligence at the edge.” Micron is one of the leading memory and storage solutions and can generate and collect data at rates and volumes not thought possible just a few years ago. Anderson highlighted that with the data economy growing at a tremendous rate along with the rise of AI and the enablement of 5G, the explosion of data is not limited to traditional applications.
The topic of memory is key in wearables as typically wearables are small-scale and require suitably sized, low power, and high capacity memory storage to collect vast amounts of data and deliver advanced abilities as we’ve previously discussed here.
It’s great to see such developments in memory from Micron as their memory cards can support various wearable devices such as smart watches, fitness devices and AR/VR equipment. Micron’s Industrial MicroSD cards can also support the growth of AI-enabled camera use cases in video security applications by providing storage specifically designed for handling continuous video data as they have a high lifetime and low error rate.
The third talk we attended was by Roberto Pellegrini, BU Manager, Reply, Miguel Blasco Engineering Director, Storm Reply, and Andrew Delamare, Manager, Solutions Architecture, Amazon Web Services as they discussed “Unlocking your IoT Data from Edge to Cloud with AWS.” This talk consisted of a panel discussion on the latest developments in IoT and the benefits customers receive by applying AWS strategies to unlock IoT data. Utilising AWS edge services can provide flexible data collection, analysis, and cloud computing, enabling the development of more smart, responsive, and cost-effective IoT applications and wearables.
Our final talk of the day was by Pierre Guiglion, AI Technical Marketing Engineer, from STMicroelectronics who discussed “The shift of AI capabilities from the cloud to the edge.” Guiglion noted that through this shift there is an opportunity for manufacturers to fundamentally improve industrial processes by applying NanoEdge AI Studio to the process.
One of the benefits we discovered is that it doesn’t require data science expertise and by utilising this new ML technology it can optimise maintenance costs, deliver innovative functions in equipment, process data, and limit risks to increase the chance of success. Users can integrate smart features quickly and easily into their equipment or wearables from its sensor-agnostic, low-code approach, combined with the capacity for cloud-independent embedded learning.
We felt incredibly grateful to hear such a wide range of perspectives and get insight into hardware innovations shaping the future. Continuous innovation is at the heart of what we do at Thrive Wearables as our aim is to turn cutting edge ideas into engaging, user-centred wearables. If you have an idea for a wearable product get in touch with us and our team of technical experts will bring your ideas to life.
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