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This guide walks you through building a Health Monitoring System using wearable IoT devices , Azure IoT Hub , Azure ML , and Azure Functions . You'll learn how to collect vital signs such as heart rate, temperature, and oxygen levels from IoT devices, send the data to Azure IoT Hub, and leverage Azure ML to predict health risks like heart disease. This end-to-end solution ensures real-time monitoring and alerting for health trends, making it a powerful tool for healthcare and wellness applications. This Health Monitoring System Architecture diagram shows the flow of health data from wearable IoT devices to Azure IoT Hub, where it is processed using Azure Functions and analyzed with Azure Machine Learning to predict potential health risks. The components involved include: User provides health data via the Wearable IoT Device . The Health Data Collector sends this data (heart rate, temperature, oxygen levels) to Azure IoT Hub . Azure IoT Hub triggers Azure Functions to proces...

Diagram Explanation 1️⃣ Raspberry Pi with a DHT11/DHT22 sensor sends real-time temperature data to Azure IoT Hub . 2️⃣ Azure IoT Hub processes incoming data and triggers Azure Functions for further processing. 3️⃣ Azure ML Model analyzes data and detects temperature anomalies (e.g., overheating or cooling failures). 4️⃣ If an anomaly is detected, Azure Functions calls Azure Communication Services (ACS) . 5️⃣ ACS sends an SMS/Email alert to the admin/user . 6️⃣ User/Admin monitors temperature data and receives alerts. This guide will walk you through building a real-time temperature monitoring system using IoT sensors (Raspberry Pi) and Azure cloud services . The system will: ✅ Collect temperature data from IoT sensors. ✅ Analyze real-time temperature data for anomalies using Azure ML . ✅ Trigger alerts (SMS/Email) via Azure Communication Services (ACS) when abnormal temperature conditions are detected. 🛠 Tech Stack Hardware: Raspberry Pi, DHT11/DHT22 Temperature Senso...

Build a Smart Home Automation Dashboard using Flask, Azure IoT Hub, and Azure Functions to remotely control devices like lights, fans, and locks. This guide walks you through setting up IoT communication, processing commands, and deploying the solution on Azure Cloud for real-time smart home management. Flow: 1️⃣ User sends a request via the Flask Web App . 2️⃣ Azure Function processes and forwards the command to Azure IoT Hub . 3️⃣ IoT Hub relays the command to the Smart Device (e.g., turn on a light). 4️⃣ Smart Device sends back a status update to IoT Hub . 5️⃣ Flask Web App receives the update and displays it to the user. 🌟 Overview This guide will help you build a Flask-based web application that allows users to control smart home devices (lights, fans, door locks) remotely via Azure IoT Hub . ✅ Features: Turn ON/OFF lights, fans, and locks using a web dashboard Send commands to IoT devices via Azure IoT Hub Process commands using Azure Functions Display real-time dev...