Think Different

  image credit researchgate IoT Data Sources for Industrial and Smart Applications IoT devices generate real-time data from various sensors. Below are some key IoT data sources and example use cases , focusing on an Arduino-based warehouse monitoring system with temperature and humidity sensors. 1. IoT Data Sources 1.1. Industrial and Smart Warehouse Sensors Temperature & Humidity Sensors (e.g., DHT11, DHT22, BME280) – Monitor warehouse climate. CO2 and Air Quality Sensors (e.g., MQ135) – Ensure air quality for workers and storage conditions. Light Sensors (LDR) – Adjust warehouse lighting automatically. Vibration Sensors – Detect abnormal equipment movements or seismic activity. RFID & Barcode Scanners – Track inventory movement. Weight Sensors (Load Cells) – Monitor stock levels in real-time. Motion Sensors (PIR) – Detect unauthorized movement in restricted areas. 2. IoT Warehouse Setup with Arduino & DHT11 (Temperature & Humidity) Components Requ...

                                                         Photo by Acharaporn Kamornboonyarush Let's compare MongoDB and InfluxDB by providing a simple example of how you can use both databases with Python for storing and retrieving time-series data. We'll use Python's official client libraries for both databases. This example will cover data insertion and retrieval operations. MongoDB Example: First, make sure you have the `pymongo` library installed. You can install it using pip: ```bash pip install pymongo ``` Here's a simple Python example for using MongoDB to store and retrieve time-series data: ```python from pymongo import MongoClient from datetime import datetime # Connect to MongoDB client = MongoClient("mongodb://localhost:27017/") db = client["timeseries_db"] collection = db["timeseries_data"] # Insert a time-...