We all are living in a technological era. Has the technology been used to its maximum to save people from getting deceased? People that get infected due to contaminated surfaces are yet not significantly reduced from past decades. We want to make a change and use the technology that people build to save people. We focus on patient safety in healthcare centers.

We would like to achieve this by reducing healthcare-acquired infections like COVID-19 on highly touched contaminated surfaces, mobile medical equipment, especially in high-risk patient ward areas. For 2000 years we’ve manually been cleaning hospital surfaces.1st Hospital Greece 2000 years ago. Killing superbugs will be used to reduce the impact of infection for vulnerable high-risk people with medical conditions.

What it does

  • MUVi infection prevention prediction system monitors bioburden contamination level in hospital rooms.
  • Will enable evidence-based cleaning intervals
  • Providing real-time visualization status of the aseptic condition.
  • Tracking sensor fitted to mobile equipment and the patient rooms that monitor tracks alerts,
  • Identification of highly vulnerable areas for enhanced cleaning.

How we built it

We used Agile Methodology and Scrum meetings (two meetings in a day) to ensure we meet checkpoints and meet deadlines. We split into two teams: Technical and Presentation Our Team names in Slack: Our main channel for communication with the Mentor was: t_lightsaberjedis_zk63 These were our private channels

  1. muviestonia_lightsaberjedis
  2. muviestonia_presentation
  3. muvieestonia_technical_private

We have built this solution using the IoT sensors embedded with long-lasting battery life ( 1 -3 years). The IoT sensors will send the data using the low power LORA network to the applications for data analysis.

Challenges we ran into

Limited time and working with people from different time zones have been challenging. But communication has kept us and linked the gap. One of the main challenges was working according to time zones. So, we worked according to 6 different time zones to get it done correctly.

Accomplishments that we're proud of

We are proud of 2 factors.

Technical achievement
  • Completed data pipeline for sensors and equipment to database and front end UI
  • Updated sensor simulation adding room occupancy counting
  • Automated scheduling via prototype infection prediction algorithm
Business level achievement
  • We found people who are interested in getting us a pilot trial in the ICU units of EU hospitals.
  • We are working on the approvals

What we learned

Working collaboratively and remotely was an important aspect that we learned. From the feedback we received from mentors, we were able to see more thoroughly from the financial perspective. I was able to find opportunities in the EU healthcare industry, so the learning will help us to prioritize and select the pilot hospitals.

What's next for Killing SuperBugs infection using advanced IoT data analysis

Within the next 3 months, we are moving towards providing clinical pilot trials to 10 selected hospitals in the EU region. We will analyze the results and target the revenue generation based on predictive analytics.

What's next for the team

We are going with the same team forward to the future development of the product and running trials in the EU and thereby ensuring patient safety to combat viruses like COVID-19.

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