• Vishali
• Gowthami pullemla

An Al-assisted system called Arogyashield was created to enhance infectious disease risk monitoring and early detection, with a focus on underprivileged and rural communities. The system takes user inputs in the form of voice recordings and medical photographs, processes them through image recognition and natural language processing (NLP), and then uses a machine learning model to analyse the results. Three risk levels-low, medium, and high-are assigned to health issues by a classifier based on Random Forest and Logistic Regression. Strong retrieval accuracy was shown by extensive examination (95.2% top-3). good recollection of important cases (91.6%) and accurate transcription of speech (94.3%). Additionally, the system incorporates a hospital alert system that offers minimal latency real-time messages for high-risk situations. Arogyashield shows how intelligent technologies can be used to increase access to healthcare in rural areas and facilitate prompt treatments by bridging healthcare gaps using multimodal, multilingual, and Al-driven triage.

"ArogyaShield: AI-Driven Diagnosis and Risk Monitoring System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.d38-d42, November-2025, Available :http://www.jetir.org/papers/JETIR2511305.pdf

"ArogyaShield: AI-Driven Diagnosis and Risk Monitoring System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppd38-d42, November-2025, Available at : http://www.jetir.org/papers/JETIR2511305.pdf