In this project we have designed IoT Based Patient Health Monitoring System using ESP8266 & Arduino. The IoT platform used in this project is Ubidots (or ThingSpeak in old version).

In IOT based monitoring project designed for keep on time track on the health status of the patient and updating to doctor at remote location anytime. With this effective device, health status of a critically ill patient can be constantly monitored. It can be used to keep track of health of aged people who frequently have heart or blood pressure issues. The IoT project developed here is built on Arduino UNO. It is interfaced with ESP8266 Wi-Fi modem to connect with an internet router and access the cloud server. The Arduino is interfaced with LM-35 temperature sensor to sense the body temperature and a pulse sensor to read pulse rate It continuously monitors the pulse rate and body temperature and updates them to an IoT platform. If any abnormalities are detected then system immediately sends notification to doctor. The IoT platform used in this project is ThingSpeak. Thingspeak has capabilities for Visualizing the collected data in the form of charts, Ability to create apps for collaborating with web services or social network and other APIs. The data from ThingSpeak to android application will send by HTTP request and HTTP response protocol. A threshold value is being set for pulse rate and body temperature. In android application there will be separate login credentials for patient and doctor. When the doctor will login, list of patients will be displayed along with two tags Patient Details and Health Status. In health status data from the Thingspeak will be fetched, doctor can check the medicine that the patient is consuming and can update is depending upon the health status. The patient can check the health status and medicine list and can also update details accordingly. Such a system consist of physiological data that stores, process and communicate through a local manner such as smart phones by using the system the health care professionals can monitor and advice their patient all the time.

Raspberry Pi project to monitor water depth in a rainwater tank using a HC-SR04 ultrasound sensor, and cross reference these to weather conditions. Logging and trend analysis via the ThingSpeak IoT platform and the python data libraries (pandas, numpy, matplotlib).

This project uses arduino online simulator (Tinkercad) with thingspeak to monitor the air quality and provide a statistical report

In this Project, I will work with Smart irrigation System that has wide scope to automate the complete irrigation system. Here I will be building an IoT based Irrigation System using ESP8266 NodeMCU Module,Arduino Uno , Soil Moisture Sensor Module and DHT11 Sensor. It will automatically irrigate based on the moisture level in the soil, Temperature and Humidity of ambient and also send the Data to ThingSpeak Server to keep track of the land condition. The System also consist of a water pump module which will be used to sprinkle water on the land depending upon the land environmental condition such as Moisture, Temperature and Humidity.

In this hands-on and interactive workshop, you will learn how to use sensors, AI, and IoT to build a smart fitness tracker using your own mobile device. Learn the basics of sensors, AI, machine learning, and IoT required for building this application. We will demystify the buzz around sensor analytics, machine learning, and IoT and show you how easy it is to build smart wearables. You will be energized and engaged while doing hands-on exercises and leave excited about IoT and wearables and taking up challenging projects in this domain. Discover how MATLAB Online™, MATLAB Drive™, ThingSpeak™, and machine learning algorithms (knn) are seamlessly integrated and used within MATLAB Mobile™. To participate in this workshop, you will need a MathWorks account (create MathWorks account).

An IoT project utilizing ESP32 integrates seamlessly with ThingSpeak & Flask to create a smart "Garbage Truck Route Optimization System." This system dynamically calculates optimal routes for collection vehicles based on dustbin location & fill status.

This project demonstrates a LoRa communication setup using multiple nodes transmitting temperature and humidity data to a central server. The server receives the data, processes it, and optionally sends it to the internet via ThingSpeak.

An ESP32-based project to monitor air quality (PM1, PM2.5, PM4, PM10, CO₂, temperature, and humidity), displaying data on an e-paper screen and optionally sending it to ThingSpeak. It needs WiFi to work, time is obtained via internet.

An IoT project using an ESP8266 to read sensor values and send them to Thingspeak.

This Project is an IOT Project of an STM32Nucleo interfacing with an esp8266/esp01wifi, that is sending data from a humidity sensor to thingspeak database, there's also two interruptions implemented.

This project uses a NodeMCU, DHT11 sensor and moisture sensor to measure temperature, humidity and soil moisture, sending the data to ThingSpeak for real-time monitoring. Ideal for indoor climate control and weather monitoring.

STM32 and ESP32 based embedded projects Real-time systems with FreeRTOS IoT and MQTT communication Sensor integration and data filtering Cloud connectivity (ThingSpeak, AWS IoT, etc.) C, C++, JSON serialization and parsing UART, SPI, I2C communication protocols

"🌊 Predict water quality in real-time using IoT and 🤖 machine learning! This project combines data from pH, turbidity, and TDS sensors via Arduino, analyzed by a Random Forest model. The Flask interface makes it user-friendly, and ThingSpeak offers visual insights.

This project uses an ESP32 to monitor the quality of grey water after filtration with cost-efficient materials like cotton and charcoal. Sensors (pH, turbidity, water level) send data to ThingSpeak, which is displayed in a Flutter app for easy monitoring and alerts.

# Air-Quality-Monitoring-System This project uses arduino online simulator (Tinkercad) with thingspeak to monitor the air quality and provide a statistical report This project can also be done without online simulation ## Components Required (ignore if you are doing it online) * Arduino Uno * 16X2 Charater LCD * ESP8266 Wi-Fi Module * MQ135 Gas Sensor ## Connections * LCD RS pin to digital pin 12 * LCD Enable pin to digital pin 11 * LCD D4 pin to digital pin 5 * LCD D5 pin to digital pin 4 * LCD D6 pin to digital pin 3 * LCD D7 pin to digital pin 2 * LCD R/W pin to ground * LCD VSS pin to ground * LCD VCC pin to 5V * 10K resistor: * ends to +5V and ground * wiper to LCD VO pin (pin 3) ## System Architecture  ### For a graphical view of connections please visit https://www.tinkercad.com/things/4bvrgNA91Dt ## Air Quality measurement * Converting air pollutant concentration 1. Converting Micro grams per cubic meter to PPM ppmv = mg/m^3 x (0.08205 x T) / M 2. Converting PPM to Micro grams per cubic meter mg/m^3 = ppmv x M /(0.08205 x T) Where, mg/m^3 = microgram of pollutant per cubic meter of air ppmv = air pollutant concentration, in parts per million by volume T = ambient temperature in kelvin 0.08205 = Universal gas constant M = Molecular weight of air pollutant ## Software and Prerequisites * Tinkercad.com: Go and signup on tinkercad.com(for online arduino simulation) if u want to complete the project online and visit this link for guidance * Thingspeak.com Firstly go to thingspeak and signup and login Then, go to "channels" section and create a new channel While creating the channel, name it as per your requirements and create only one field named "Air Quality" Save the channel After that, go to "API keys" tab under your created channel and save the given API key! ## To understand the code please read the guide.docx file! ## Note: Because of the firewall or an unkown issue i wasn't unable to connect to the thingspeak server but if you are doing it on a hardware it can be easily done! Any further contribution is highly appreciated!

This project has been designed for Arduino touch free-challenge Functioning: Usually, in malls or supermarkets, many people touch certain objects in aisles and it is really hard to monitor each object and sanitise each aisle individually. Most of the times, manual sanitisation is completed after each day and individual sanitisation of each aisle is not possible. Sometimes it happens that the food-aisle is more contaminated and the clothes-aisle is less contaminated, hence extra care is required for monitoring and sanitisatio of food-aisle. But such a monitoring solution is not possible manually. Therefore, I decided to make an autonomous solution based on TinyML deployed on Arduino Nano 33 BLE Sense. The person-identification model is highly accurate and uses an arducam which can be used in 5mp or 2mp variants. In solutions that contain ultrasonic sensors, or Lidar sensors, the readings or measurements are not accurate and can send false readings. Hence, the person detction model uses person recogition technology based on TensorflowLite framework. When, 1-50 people are detcted, a green light is switched on which means that the area is yet secure. When, 51-75 people are detected, a yellow light is flashed which means that awareness is required. When, 76-100 people are detected, a red light is flashed which means that people need to carefully touch objects and only touch those objects which are required. When 101-110 people are detected, the UV sanitisation system is activated which sanitises the complete area and objects are secure again. The count is again reset to 0 and the cycle is looped. The people vs Time graph is potrayed on the ThingSpeak web app where mall owners can track the time when the crowd is more or less and accordingly maintain more awareness during peak timings.

A small project to show data from weather sensors from Thingspeak using Chartist and Django.

ESP8266 project for measuring Humidity, Temperature etc and sending it to an SSD1306 OLED and Thingspeak

This project contains an ESP32 sending Temperature and Humidity readings to Thingspeak and a locally hosted database.

HTML5 app that interfaces with ThingSpeak for home control. It is used by my Arduino IoT class project

PlantSpeak is an IoT project that publishes sensor data from an "ESP-32 Soil Moisture Sensor Module" to ThingSpeak.

This is project build by Muhammad Irsyad Yunus. Build on ESP8266 and using Thingspeak database to display the data through online form.

This Project has a basic demo with analog sensor, where the data from the analog sensor are visualized in the thingspeak api

This is a project which uses esp8266 and arduino UNO along with ultrasonic sensor to detect the distance and send it to blynk mobile app and thingspeak channel.

In this project, we use Raspberry Pi 4 as our Access Point which receives data from many NodeMCU's connected to DHT11 and sends the data to ThingSpeak Cloud

This is a beginner friendly IoT project which uses ThingSpeak cloud platform to collect and analyze sensor data. Based on the obtained sensor data, we actuate other IoT devices.

LabVIEW-based PFE project for real-time monitoring of a compressor room. Includes data acquisition via OPC UA (Raspberry Pi), storage in SQL Server, alarm system, and remote visualization using ThingSpeak IoT platform.

A comprehensive, microservice-based IoT system for home security monitoring. This project simulates a network of sensors and actuators to detect and respond to potential intrusions, providing real-time updates through a web interface, a ThingSpeak dashboard, and a Telegram bot.

The Temperature and Humidity Monitoring System is an IoT project utilizing Python and a DHT22 sensor to gather real-time temperature and humidity data. This data is sent to ThingSpeak for easy visualization and analysis, making it a great educational tool for IoT enthusiasts.