Vídeň - Sever
Video
Project / product name: iseeyou
Link to the project: https://github.com/LukasCelnar/iseeyou.git
Team leader: Matouš Paleček
Challenge: 3. ICU Surveillance System
Problem: Hospitals are heavily reliant on manual methods for monitoring patient activities and staff visits, consuming valuable time and resources. This manual approach leads to inefficiencies in patient care and delayed responses. The lack of an automated, efficient system for tracking and data collection also hinders the potential for advanced patient monitoring solutions.
Solution: iseeyou utilizes existing CCTV infrastructure in hospitals to efficiently track patient movements and staff visits. This approach not only aids in immediate patient monitoring but also serves as a critical data collection tool. By recording key data snippets, iseeyou sets the foundation for hospitals to potentially develop more advanced monitoring systems in the future.
Impact: The implementation of iseeyou enhances patient safety by ensuring regular monitoring and timely interventions. In the longer term, the data collected can be instrumental in refining patient care practices and procedures. Immediate benefits include better staff accountability and improved patient outcomes, with the added potential of contributing to future healthcare innovations.
Feasibility & financials: With a swift implementation period of 1-3 months, iseeyou is both practical and cost-effective. It leverages existing hospital infrastructure, thereby minimizing additional costs. The solution offers significant financial benefits by improving patient care efficiency and laying the groundwork for future enhancements in hospital monitoring capabilities.
What is new about your solution?: iseeyou stands out as a solution that not only addresses current monitoring challenges but also strategically collects data for future advancements. It offers an innovative approach to patient care, enabling hospitals to build a valuable dataset. This positions iseeyou as a key enabler for future enhancements in patient monitoring, potentially through AI technologies.
What you have built at the hackathon - text explanation + code (e.g. GitHub link): The entire algorithm, as presented in the video.
https://github.com/LukasCelnar/iseeyou/blob/main/iseeyou.ipynb
What you had before the hackathon, please mention open source as well: Nothing. We didnt use any external code.
What comes next and what you wish to achieve: We would love to see it implemented in IKEM.