In the prior post we have built the history layer, now it is the time to look into its data. The idea is to get some simple interface providing interactive access to any data we want. Let’s try to achieve that with the leading open source software for time series analytics, Grafana. Installation I installed Grafana on my development machine using Docker. How to install Docker can be found here.
History Layer There are 5 access data layers introduced in my elder post Building Sensor Network: with BigClown: Current, History, Integration, Machine Learning, Reporting. And we have already utilized the first one and the last one in the post IoT Doorbell: with BigClown. Now it is the time to look into the History layer. Time series database Storing, maintaining and accessing historical data is always expensive, so it is worth spending some time on finding the most effective way how to cope with that.
SMS gateway Before designing some simple flows in Node-RED, lets’s create functional SMS gateway. The critical communication channel in the sensor network I build and describe in my blog. Having SMS gateway, we can create first practical use cases utilizing the data in access layers. For now, just the first access layer, the MQTT. I bought a cheap 3g USB dongle Huawei E3531 and inspired by article Sending SMS on a Raspberry Pi started the installation.
Battery Monitor over MQTT It can sound quite obscure to publish Computer Battery status over MQTT. But I think it is on the contrary, absolutely essential thing. Let me explain. In fact, I was about to write a post about smart alerts, to move finally to something really practical after so many posts focusing just on building the sensor playground. Honestly, I postponed such topic already several times. Always something popped up, what was absolutely essential to cover before moving further.
Neurio Neurio Home Energy Monitor is one of my smart IoT sensors which offers nice cloud app. This one monitors the detailed house power consumption. When I started to build my own sensor network independent of the cloud availability, I was pleased to find out that, not like Netatmo sensors, Neurio offers also local access to the actual measurements. Then the task was clear, I need to have power consumption information available through MQTT.
Jablotron Futura Futura is a heat recovery unit, sort of the heart of a house ventilation system and as such, it can introduce complex information about the indoor air quality into my sensor network. But to be honest that fact wasn’t the main driver for its integration. The driver It was one issue I had with the unit and couldn’t fix it within the standard product support. The behavior of the units depends on the settings you give it.
The Idea There are many situations when you miss a delivery or a visitor while being in the garden, garage, workshop or just watching a movie or listening music. Of course, there are wireless doorbell extenders, but I prefer system solution. The idea is simple, to integrate the standard wired doorbell into my sensor network so each doorbell ring generates MQTT message as any other sensor. Then there are unlimited options how to utilize the doorbell events.
The Motivation I am definitely not a hardware guy. Never was and never will be, but nevertheless, I enjoy building my smart house and garden. I started with not that smart weather station and moved its data to the cloud in my first blog and later used some open API of smart IoT products like Netatmo Cameras, see the article here. Unfortunately, there are some limitations always. It is hard to customize the specialized products and mostly it is only possible to access the data from the cloud.
The ETL Script environment We are going to access Netatmo cameras using Netatmo Connect API which is basically REST API providing JSON responses. I think the best scripting environment for work with dictionaries, lists, and sets is Python. And there is even nice client simplifying the communication with this API in Python netatmo-api-python provided by Philippe Larduinat. Well, it wasn’t hard to decide and I installed the latest version of 3.
The Idea I have few smart Netatmo cameras, both indoor and outdoor. And it is quite logical to integrate them into my personal Datawarehouse. There is even nice open API supporting such intention. The goal is to load event data into detail layer and store the snapshot photos in Google photos using the Google Backup and Sync. Then, of course, somehow link the data with the photos. The Data Model Concept This time we are going to face bit more complicated interaction with the source system.