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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...

🔷 Diagram Explanation 👤 User interacts with the Spring Boot application through HTTP requests . 📂 AzureFileController handles user requests and forwards them to ⚙️ AzureFileStorageService . ⚙️ AzureFileStorageService communicates with 📦 Azure File Storage to perform: 📤 Upload files 📄 List files 📥 Download files ❌ Delete files ☁️ Azure Cloud hosts the 📦 Azure File Storage , which securely stores the files. Azure File Storage provides a cloud-based fully managed file share system that allows applications to store and manage files in a distributed environment. In this guide, we'll build a Spring Boot application that interacts with Azure File Storage to: ✅ Upload files ✅ List files ✅ Download files ✅ Delete files 2. Prerequisites ✔️ Azure Subscription – Sign up here if you don’t have one. ✔️ Azure Storage Account – Create one via the Azure Portal . ✔️ Spring Boot (3.x) application with Spring Web dependency. ✔️ Azure Storage SDK ( azure-storage-file-share ). 3. ...

Diagram Explanation 📌 User sends HTTP requests to QueueProducerController . 📌 QueueProducerService pushes the message into Azure Queue Storage (cylinder). 📌 QueueConsumerService polls messages from Azure Queue Storage and processes them. 📌 After processing, the message is deleted from the queue. Azure Queue Storage is a cloud messaging service that enables applications to communicate asynchronously by passing messages. In this guide, we'll implement a Spring Boot Producer to send messages and a Spring Boot Consumer to retrieve and process them. Prerequisites Before you begin, ensure you have: ✔️ Azure Subscription (Create one here ) ✔️ Azure Storage Account with Queue Storage enabled ✔️ Spring Boot installed (Use Spring Initializr ) ✔️ Java 17+ installed ✔️ Maven/Gradle for dependency management Step 1: Create Azure Storage Queue 1️⃣ Log in to the Azure Portal 2️⃣ Search for Storage Accounts → Click Create 3️⃣ Provide Subscription, Resource Group, and Storage Acco...

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...