Pitch-In is pleased to be co-hosting the ongoing programme of events for Newcastle IoT Meetup alongside Newcastle University Business School, sponsored by GoTo50.ai and Newcastle University.
Typically held every on the first Tuesday of every month the meetup provides a platform for discussions around IoT and AI development and implementation across Newcastle and the wider region. It gathers people, who are involved in the IoT ecosystem, interested in the adoption of technology or looking for solutions to the delivery of automation and intelligence.
April’s meetup – an overview
Provided by Paul Wealls, event organiser
The recent April meet-up, hosted virtually, featured a talk from Oliver Hamilton, Director of Computer Vision at COSMONIO. COSMONiO is a software development company developing AI-based systems focusing on computer vision and image processing. COSMONiO designs AI systems extracting visual information from images based on self-learning algorithms. The company runs research and development labs focusing on intelligent vision systems, medical technologies based on deep learning and computer vision for life sciences.
Oliver Hamilton presented NUOS machine learning interactive platform working without writing a single code. The platform automates visual inspection tasks, such as the detection, segmentation and classification of instances on images or video, anomalies identification, counting and localisation of instances. Oliver demonstrated how the system works when it is applied for object detection. For the system to build a dataset, a user needs to capture and annotate objects. This can be done by drawing bounding boxes on images or video or by using an AR kit to capture a 3D model of the object in space. The generated dataset is used by the system for self-training, which might take several rounds. Each round of training requiresthe edits and feedback from the user to improve the task implementation through incremental self-learning. Oliveralsoexplained how the platform can be deployed to edge computing devices.
The all-inclusive NUOS system is capable to solve complex pattern-recognition problems in the fields of biology, health, defence, industrial inspection and space exploration. For example, NUOS can be a time-, labour- and cost-efficient solution for detecting road traffic offences captured on outdoor cameras. By tasking the deep-learning machine, the system can be trained to detect and capture only the anomalies, without the need to record the entire chain of events. The deployment of the system can save time spent on manual data inspection, reduces the amount of recorded data and associated costs.
To participate at the future IoT meet-ups and learn more how advances in AI and IoT can benefit organisations of different sectors, follow the schedule of events here.