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IoT Meetup May 2020 / Pitchin Webinar Report

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  • 2020-05-05
2020-05-05

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IoT Meetup May 2020 / Pitchin Webinar Report

IoT Meetup – May 2020

On Tuesday, the 5th of May, in virtual space Newcastle & Manchester Meetup connected all those who are interested in the use and the development of IoT and AI. The online event was co-hosted by Pitch-In Project and sponsored by Newcastle University and www.goto50.ai. The meetup hosted a presentation by Rodolfo Lomascolo from Pervasive Technologies (https://pervasive-tech.com) about vision and machine learning solutions, which can have an application against the propagation of COVID-19.

Pervasive Technologies is a company located in Barcelona, which specialises in the development of predictive solutions based on artificial intelligence, machine learning and deep learning technologies. Having clients mainly in European countries from retail and different industries, the company develops intelligent technologies for processing images and videos that improve business operations. Technically, the company focuses on visual data that is analysed on the edge by connecting devices to available cameras in corporate, public and industrial settings. The data fed into the technology provides actionable insight and instant outputs that can be used for improving company processes. The main types of industrial solutions include personal protection equipment (PPE) auditing, behaviour analysis, object classification and sorting, vehicle traffic analysis, ICR (intelligent character recognition) in extreme industrial environments and ICR in the office environment for document analysis and processing. vRodolfo Lomascolo presented Proppos Self-checkout and PPE Audit and Detection technologies and the application of these technologies for the prevention and control of the spread of COVID-19. Proppos Self-checkout is designed to be used in public social places, such as canteens, cafeterias and restaurants to expedite the shopping process, minimise the number of on-site service workers and eliminate queues. The technology represents an intelligent and autonomous self-checkout powered by computer vision and deep learning algorithms that recognise any kind of product without the need to scan them. For business, the implementation of such a solution brings financial value due to the reduction of operational costs and the optimisation of production. Customers benefit from a greater shopping experience and efficiency. PPE Audit and Detection is an artificial intelligence solution, automating the inspection of equipment worn by industrial workers. AI-embedded devices implemented at manufacturing, construction and industrial sites help reduce the risks that such complex environments entail. They help improve inventory, reduce costs and improve health and safety compliance procedures.

The demonstrated technologies found a timely application in the COVID-19 situation. The deployment of AI-based processing devices and cameras in public places can help increase public health and safety by measuring, alerting and reporting on human body temperature. Technologies can control social distancing through the detection of the distance between people. The devices can spot the availability of facial PPE - masks and glasses - on people facing cameras. With the real case examples, one can see how AI can have a palpable impact by mitigating the effect of the pandemic.

To participate in future IoT meet-ups and learn more about how advances in AI and IoT can benefit people and organisations, follow the schedule of events here at the IoT North meetup web site: https://www.meetup.com/meetup-group-JfzuesuE/ or at our Pitchin In one: https://ebusiness.ncl.ac.uk/projects/pitchin-iot-ecosystem/iot-meetup.php

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Ebusiness @ Ncl

E-business is concerned with using the Internet and related technologies to integrate and redesign an organisation's internal activities, processes and external relations, and create new ways of working that are significantly different from, and very often far superior to, what was possible or even conceivable in the past.
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