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This post features videos that I published to my YouTube channel in the series "IOT with Raspberry Pi ". This basically contains 4 videos around Raspberry Pi that show how to use Raspberry Pi as an IoT device. It starts from interfacing sensor to publishing the sensor data to cloud server using protocols like REST or MQTT. For the entire project I have used JAVA and on top of that used various libraries for specific tasks like Pi4J, Unirest, Eclipse PAHO etc (Links provided below). If you have watched any of the videos you might know that the series is divided into 4 parts namely:
- DS18B20 Sensor interfacing with Raspberry Pi.
- Publishing data to Thingspeak using REST.
- Publishing data to Thingspeak using MQTT.
- Completing the project.
So let's check out how to do so.
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1. DS18B20 Sensor interfacing with Raspberry Pi.This video is the first part of it where we will see how to interface DS18B20 one wire temperature sensor with Raspberry Pi by using JAVA with the help of the pi4J library.
2. Publishing data to Thingspeak using REST.This video is the 2nd in the series where we will see how to publish or send sensor data using REST API to cloud. And in this, we are using ThingSpeak as cloud service to publish data. HTTP calls for REST API are done using Unirest lightweight HTTP client library. In the next video, we will see the same by using MQTT.
3. Publishing data to Thingspeak using MQTT.This video is the 3rd in the series and is about how to publish or send sensor data using MQTT API to cloud. And in this, we are using Thingspeak as cloud service to publish data. Publishing Data using MQTT is done using Eclipse PAHO lightweight library. MQTT is a simple lightweight publish/subscribe protocol that can be used over TCP instead of going for HTTP as MQTT is power friendly and bandwidth friendly as compared to HTTP. So it fits perfect for IoT applications. If you are interested in more about it, you can check some docs linked below.
4. Completing the project.If you have not checked above videos please check those first before checking out this video. This video is the final one in the series where we will complete the project by combining the codes developed in the earlier videos. We will make the application such that we can decide te API that we will be using to publish the data to Thingspeak.
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