Integration of Telemedicine and Digital Environmental Monitoring for Early Detection of Environmentally Related Diseases in Remote Areas

A Literature Review

Abstract

Environment-based diseases such as Acute Respiratory Infections (ARI), diarrhea, malaria, and leptospirosis remain major causes of morbidity in remote areas of Indonesia. This condition is exacerbated by limited access to healthcare facilities and the lack of real-time environmental monitoring systems that support early disease detection. This study aims to design and analyze an integrated model of telemedicine and Internet of Things (IoT)-based digital environmental monitoring systems to improve the early detection of environment-related diseases. The study employed a systematic literature review using the PRISMA protocol on 15–20 references from journals indexed in Scopus, PubMed, and SINTA published within the last 5–10 years, complemented by implementation case studies in remote regions of Indonesia. The analyzed parameters included PM2.5 levels, water quality indicators (E. coli, turbidity, and pH), temperature, relative humidity, vector presence, and telemedicine clinical responses. The literature synthesis indicates that the integration of telemedicine with digital environmental monitoring has the potential to improve the early detection of environment-based diseases compared to the use of each system separately. The integrated model, which applies automatic threshold mechanisms such as PM2.5 > 100 µg/m³, E. coli > 100 CFU/100 mL, and humidity > 80%, enables the system to provide earlier and more proactive alerts to healthcare workers through telemedicine applications. Furthermore, this integration is expected to reduce diagnostic delays, improve healthcare service efficiency, and lower referral costs in remote areas.