Building Jarvis – Concerns & Solutions
I was going through this article by Mark, on his personal challenge – “build a simple AI to run my home — like Jarvis in Iron Man!”
His idea was to build a system, which allowed his phone and computer to control home, including lights, temperature, appliances, music and security, that also learns personal tastes and patterns.
Before building AI, first thing was to get data from all sensors, which includes smart as well as legacy sensors. And according to him, this was a bigger challenge.
Excerpts from Mark Blog Post
Before I could build any AI, I first needed to write code to connect these systems, which all speak different languages and protocols. We use a Crestron system with our lights, thermostat and doors, a Sonos system with Spotify for music, a Samsung TV, a Nest cam for Max, and of course my work is connected to Facebook’s systems. I had to reverse engineer APIs for some of these to even get to the point where I could issue a command from my computer to turn the lights on or get a song to play.
Further, most appliances aren’t even connected to the internet yet. It’s possible to control some of these using internet-connected power switches that let you turn the power on and off remotely. But often that isn’t enough. For example, one thing I learned is it’s hard to find a toaster that will let you push the bread down while it’s powered off so you can automatically start toasting when the power goes on. I ended up finding an old toaster from the 1950s and rigging it up with a connected switch. Similarly, I found that connecting a food dispenser for Beast or a grey t-shirt cannon would require hardware modifications to work.
For assistants like Jarvis to be able to control everything in homes for more people, we need more devices to be connected and the industry needs to develop common APIs and standards for the devices to talk to each other.
I now look back and think, if only I had met Mark 6 months ago when he was addressing the crowd at MWC in Barcelona. Had he stopped over at our booth, I am confident that we would have worked with him to solve this problem. I know I am sounding arrogant, but I guess that’s the confidence that I have in our product.
This is exactly the problem we had foreseen 2 years ago in the fragmented market of different creators of Sensors, Gateways and Clouds.
This led to the birth of our IOT gateway, which actually simplifies the solution of working through the problem which people like Mark are currently facing.
The key challenge in the real world is that most of the operating sensors work on legacy protocol. Achieving standardization will solve the problem, however, it will require software and hardware updates on these sensors which not many are ready to do.
The biggest challenge is to effectively and efficiently get data from various sensors, aggregate it and then send selective data to the cloud.
We launched our first version of the IOT gateway at MWC – Barcelona. Today we have it deployed at multiple client locations.
Our gateway supports multiple old school protocols like Modbus, SNMP, OPC, MQTT, REST and ZigBee. This allows horizontal integration of sensor protocols, and also supports triggered alert management to control various sensors and perform actions as well. The beauty is that it works in occasionally connected environments too. The gateway also supports edge analytics and edge computing, which will empower the client to decide what data needs to be sent to the cloud of their choice, which further reduces the cloud computing costs.
What we identified as pain points in implementing IOT related technologies, most of the organizations now relate to it.
We would love to hear from you about anything that is IOT and queries on our gateway.
Do get in touch with us also if you would like to work and collaborate with us.
We are a hardware agnostic software gateway, working with various System Integrators, OEMs and Sensor Manufactures to provide most suitable IoT solutions.
I have originally written this post on Winjit Canvas