Kubernetes is the leading platform for running self-healing containerized applications with fine-granular configuration, access, and security settings. Working with a managed Kubernetes distribution practically for more than 2 years, I decided to prepare for the various certifications to facilitate my learning. What could be a better approach than to start exploring Kubernetes from scratch? Learning about the components and their interactions, see the various Kubernetes distributions and perform installations on on-premise or cloud infrastructure.
Your IOT home network consist of different sensor that provide data about the environment related to different aspects, such as temperature and humidity in the air, the current level of your heater, or other binary data. And interesting and versatile extension are motion sensors. When properly calibrated, meaning that they do not send false positives, they can be helpful in many ways: Detect presence of persons (or animals!) to trigger other sensors, controlling the light, start to play music, or well raise an alert.
A complete IOT stack running on a Raspberry Pi is an effective way to integrated different sensors for home automation. In the last articles, we learned how to manually add a temperature/humidity sensor to the home network. By using PlatformIO, we manually flash the sensor, then choose available library for interacting with a sensor, and adding additional libraries to communicate with MQTT and send correctly transformed JSON data. We have complete control over all these steps, and can configure every single character that the sensor outputs. In addition to this manual way, there are great frameworks to flash and install utility programs to sensors, and also great platforms that access several sensors and show the measurements graphically as well as giving you direct interaction with these sensors.
A complete IOT stack running on a Raspberry Pi is an effective way to integrated different sensors for home automation. In the last articles, we learned how to manually add a temperature/humidity sensor to the home network. By using PlatformIO, we manually flash the sensor, then choose available library for interacting with a sensor, and adding additional libraries to communicate with MQTT and send correctly transformed JSON data. We have complete control over all these steps, and can configure every single character that the sensor outputs. In addition to this manual way, there are great frameworks to flash and install utility programs to sensors, and also great platforms that access several sensors and show the measurements graphically as well as giving you direct interaction with these sensors.
In my blog series so far, we covered how to setup the essential tools for transforming and capturing IOT data: MQTT, NodeRed, and InfluxDB. Now we will use these tools to actively collect data. The first sensor to be added is the temperature and humidity sensor DHT22. Its connected to an ESP8266 board. To flash and program it, we will use PlatformIO.
In my IOT Stack, a Raspberry Pi with an external connected disk serves as a SAMBA server. Before installing the system, I wanted to see the performance differences of various disk, their read speed, and their local and remote, via SAMBA, write speed.
In this article, I show how to write a simple heartbeat script that runs regularly on your laptop, desktop computer or IOT device to signal that it is still operational. To store and process the data, we need an IOTstack consisting of MQTT, NodeRed and InfluxDB - see my earlier articles in the series. The device from which we measure the heartbeat needs to be able to run a Python script.
A custom IOT stack running on a Raspberry Pi is an effective way to start with adding and reading sensor data or the entry to home automation. The first article in this series showed how to install a complete stack of IOT software, namely MQTT for receiving, NodeRed for transforming, and InfluxDB for storing IOT sensor data. In addition, an optional installation of OpenMedia Vault turns the Raspberry Pi into a SAMBA/NFS share. The basics of the stack are ready, and now we can add additional sensors and software step-by-step.
A custom IOT stack at home delivers a handy way to publish and record data from a wide variety of sensors. With additional software, you can visualize the data, access dashboards remotely, and even control some sensors. All you need is a Raspberry Pi 3B+ or 4 and a SSD Disk. For about 110€ - 150€ hardware costs and 1,5 - 2,5€ monthly power cost you can build and maintain your own IOT stack at home! This article covers everything to get you started.
It’s been more than a year working on my robot RADU. I could not get all of its goals fulfilled, and sadly, the robot is not autonomous. The journey itself was intricate, challenging, mostly fun with some rough edges. This article summarizes the project, recaps the goals and their fulfillments, and presents the hard lessons learned. It’s not easy to talk about failure, but I hope that you can take some knowledge from this description and make other decisions when working on similar projects.
