Publication Search

70,857 articles from 624 journals · 1,760 citations tracked

Showing 1-2 of 2

Analytics

Simangunsong, Putra Torang; Sihombing, Yehezkiel; Ridwan, Achmad

Dinamik 2026 Universitas Stikubank

Since 2022, the application of the Internet of Things (IoT) in the healthcare sector has grown significantly, marked by the increasing adoption of wearable technology, artificial intelligence (AI), machine learning (ML), and blockchain integration. Research highlights India and China as leading contributors in this domain. IoT enables real-time monitoring of chronic diseases, tracking of patient vital signs, and detection of health protocol compliance. Integrated systems such as Monit4Healthy and RADAR-IoT support personalized medical recommendations and cross-platform interoperability. However, key challenges persist, including patient data privacy and security, system interoperability issues, data fragmentation, and barriers to user acceptance due to cost, digital literacy, and device comfort. Proposed solutions include blockchain for secure data sharing, adaptive congestion control for network performance, and user training to improve technology adoption. Therefore, successful IoT deployment in healthcare requires a comprehensive approach that addresses technological, social, ethical, and sustainability aspects to achieve an effective and inclusive transformation of health services.

Sahuri, Mohamad Abid; Hadidjaja, Dwi; Wisaksono, Arief; Jamaaluddin, Jamaaluddin

Dinamik 2021 Universitas Stikubank

Monitoring realizes efforts to improve the quality of health services. To obtain information on patient condition data during treatment. The monitoring process is done manually. So that it has an impact on the service and condition of the patient during treatment. The design of monitoring the patient's body temperature and heart during treatment with IoT can be controlled through the NodeMCU sensor ESP8266, MLX9014, MAX30100 sensor and Arduino IDE software program. Furthermore, it can detect the patient's temperature and the patient's heart rate during treatment. And processed by the NodeMCU ESP8266, the data from the two sensors is displayed on the SSD1306 OLED LCD and also to the smartphone of the medical officer on duty via Blynk. In order for the tool to work properly and optimally, it is necessary to adjust the pin placement so that it can work optimally. The problem of internet connection interference causes delays, resulting in a mismatch between the measurement of the test equipment and the standard tool. Data values are taken with an accuracy of 70%-93% for the MAX30100 sensor, for the temperature sensor it is close to optimal with a value that is read on a standard tool with an accuracy of 97%-99%.