Internet of Thing-based ambience automation for optimizing patient's comfort

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Abstract

There have been efforts to automate internal temperature inside hospital premises. However, none took a patient-centric approach. Therefore, there has been a significant research gap in automating the ambience within hospital buildings, keeping the patient's comfort level at a focal point. The objective of this proposed system is to utilize a reinforcement learning (R L) approach to maximize a patient's comfort level by regulating the thermal parameters of his/her ambience. A machine learning model is first trained with the statistical data for several unique health parameters and their corresponding thermal comfort points for a wide range of individuals. When it encounters a patient, the system first reads the medical condition and then utilizes its Internet of Things (IoT) devices to control the smart thermostat to start regulating the environmental parameters of the patient's room. After going through frequent attempts to optimize the ambience for a particular patient, the system starts to learn from its error. It capitalizes on the previous decision it made each time. Thus, the system can identify the perfect environment for each patient. As a result, the proposed system will benefit the intended patients and lessen the efforts that the on-duty doctors and nurses should put in. The proposed system is equally effective in a normal room with thermostat facilities, as it is primarily trained with the data from the 'ASHRAE Global Thermal Comfort Database II'.

Original languageEnglish
Title of host publication2024 20th IEEE International Colloquium on Signal Processing and Its Applications (CSPA 2024)
EditorsRamli Adnan
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages287-291
Number of pages5
ISBN (Electronic)9798350382310, 9798350370751
ISBN (Print)9798350382327
DOIs
Publication statusPublished - 2024
EventIEEE International Colloquium on Signal Processing and its Applications 2024 - Langkawi, Malaysia
Duration: 1 Mar 20242 Mar 2024
Conference number: 20th
https://ieeexplore.ieee.org/xpl/conhome/10525259/proceeding (Proceedings)
https://www.aconf.org/conf_194153.html (Website)

Conference

ConferenceIEEE International Colloquium on Signal Processing and its Applications 2024
Abbreviated titleCSPA 2024
Country/TerritoryMalaysia
CityLangkawi
Period1/03/242/03/24
Internet address

Keywords

  • Artificial Intelligence (AI)
  • Hospital Automation
  • Internet of Things (IoT)
  • Machine Learning (ML)
  • Patient Comfort
  • Smart City

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