In March 2020 the world was plunged into lockdown due to the COVID-19 (SARS-COV-2) pandemic. Our team quickly began to focus our time on COVID-19 to help understand and fight the pandemic, our second official research project was born: Peter Moss COVID-19 AI Research Project.
The Covid-19 AI Research Project is an Asociacion De Investigacion En Inteligencia Artificial Para La Leucemia Peter Moss research project, with the goal of creating open source technology such as Robotics, Artificial Intelligence, Virtual Reality and Internet of Things to assist in the fight against the COVID-19 (SARS-CoV-2) pandemic.
The COVID-19 situation is worsening globally, with 7,628,687 confirmed cases and 425,330 deaths globally as of 13th June 2020. As the first wave continues to kill hundreds of thousands of people across the globe, governments push to open up their countries to save the economy, and the lives of the people are being put at risk.
Organizations around the globe continue the fight to help stop the pandemic through the use of technology. Data analysis, Artificial Intelligence, 3D printing and the Internet of Things are just some of today's modern technologies that are being implemented to help medical institutions in the frontline fight against the pandemic.
Through our social media outlets we share facts based on our research, and other vetted information from around the globe. We believe the public has right to know the real story.
Our research project focuses on open-source, modular technologies that make up an intelligent network allowing hospitals and medical centers to be in complete control and ownership of their data, whilst evolving the out of date technologies that are widely used today in the medical industry.
On March 18th, team member Dr Amita Kapoor published an article, COVID 2020 — A data scientist perspective, based on her research on the progression of COVID-19. Soon after this work was referenced in the peer reviewed paper: Covid-19 spread: Reproduction of data and prediction using a SIR model on Euclidean network by Kathakali Biswas, Abdul Khaleque, and Parongama Sen.
Our team continued to work on projects for early detection and data analysis and attracted a number of volunteers that are now part of our permanent team.
On March 28th, President, Adam Milton-Barker was admitted to Parc Tauli Hospital, Sabadell as a potential COVID-19 patient. During his stay in the hospital Adam was confined in the ICU reception with a mixture of COVID-19 and potential COVID-19 patients due to the lack of beds available in the hospital. Adam was concerned with the amount of time that hospital staff were being exposed to the virus, and an idea began to form for using robots to reduce the risk for medical staff in hospitals that were dealing with the pandemic. The concepts for were born.
From this idea, HIAS - Hospital Intelligent Automation System - a local server and intelligent network for hospitals and medical centers, EMAR - a tele-operated robot designed to reduce medical staff's exposure to contagious diseases such as COVID-19 and other dangerous situations we may face in the future, and EMAR Mini were born.
In April we teamed up with Simeon Pieterkosky CVO and founder at Aquaai, Simeon joined us as Robotics Product Designer to help us take EMAR through the design and manufacturing stages.
In May we teamed up with Plamenlancaster: Professor Plamen Angelov from Lancaster University/Centre Director @ Lira, & his researcher, Eduardo Soares PhD. PlamenLancaster pioneered eXplainable Deep Learning and created the SARS-COV-2 Ct-Scan Dataset, a large dataset of CT scans for SARS-CoV-2 (COVID-19) identification. Our team are working on open-source, real-world diagnosis systems based on xDNN and the SARS-COV-2 Ct-Scan Dataset to help fight the COVID-19 pandemic.