Skip to main content

An service option to interact with Arlo cameras

Interacting with the Arlo system is very attractive for who acquired the hardware and enjoy all the benefits of these equipments. Which by the way are very good, flexible and full of good properties.

To interact with this system with a developer's perspective I found two interesting python-based projects.

Python-arlo: https://github.com/tchellomello/python-arlo
Arlo: https://github.com/jeffreydwalter/arlo

Both propose different features but Python-arlo has a good documentation and structure of its API.

The objective for this integration is to support applications from Google Assistant, for this reason I  integrated the service into an App Engine flex env project. I included flask as an interaction framework and with this I have the option to use a service interface.

This would be our ideal architectural map:
We looking for continue with the application initiated from:

Hey Google ... Where is my dog?



* Of course we will have to implement the logic creating various intents into the agent from  DialogFlow. [you can see more details in this article "Google Assistant, simpleness of interaction to call a webhook"]
Let's see a simple method used in the service:

Here [ArloCamService] can see the initial version of the service.

Creative Commons License
An service option to interact with Arlo cameras by Nicolas Bortolotti is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Comments

Popular posts from this blog

Cloud Platform & Communities summer experiences in Switzerland & Italy

A couple of weeks ago with the European developers communities team we started activities with some new communities specialized in Machine Learning & Cloud Platform.  We also participated in some activities and as part of this initiative, we visited two communities with a practical program proposal  based on Cloud Technology. Cloud Study Jam . We shared a very nice activity with SOAI chapter in Zurich . Here we present the basic elements of the Cloud Study Jam proposal and we also explored a workshop with the introduction to Cloud ML engine. Cloud Study Jam Overview: *a core element of Cloud Study Jam format is the utilization of qwiklabs platform to provide tech tutorial & online labs. Cloud Study Jam, workshop "Cloud ML Engine: Qwik Start": In addition to that, we shared another very nice activity with Machine Learning Milan . Similar approach with Cloud Study Jam Overview and then we provided a workshop related to AutoML Vision. Cloud Stud...

Model Top-Down Analysis in software products.

In this paper will discuss an approach from the environmental variability of presentation software solutions. Focusing on the concept of software product family. If we play the role of architects:           How many times we try analyzing common feature in different forms of presentation?           How many times have we requested a mobile solution attached to our traditional solution?           Are simply the decisions to implement new presentations of the software solution? Here is an introduction to the concept…. Software organizations are building a product vision characterized by the development and evolution of product families instead of creating a specific software product for a given client. This trend is driven by several factors such as, business strategy, diversity computing devices and reuse of software components in complex software systems. Howeve...

Community centered care data analysis, times of Covid-19

For the past few weeks, the global health emergency caused by Covid-19 has put many questions in my thoughts, from general to more specific in many dimensions. We all know that we should prepare better in the future and this morning reviewing the concept of community centered care “ At the Epicenter of the Covid-19 Pandemic and Humanitarian Crises in Italy: Changing Perspectives on Preparation and Mitigation ,(2020), Nacoti, Ciocca, ... ” added by the hospital in Bergamo Italy, sparked my interest... how to be prepared, how potentially implement and be smart into the distribution, finally using data from Korea( KCDC  and DS4C ), I started analyzing looking for responses. From the data analysis perspective if we can understand the entities and important variables geographically distributed in a region, we can analyze the activity of this approach at least in theory dimension. Also with an analysis of infection-cases we can explore the more affected regions and maybe create a d...