Stacey on IoT | Internet of Things news and analysis

July 19, 2022 by Stacey Higginbotham 2 Comments

If we want to build a world that doesn’t require an internet connection but can still make use of ubiquitous sensors, as Alasdair argues above, then we need smarter sensors. For an idea of what that might look like, I consulted with Pete Warden, an expert in machine learning.

Warden is the former CTO of Jetpac, a company purchased by Google in 2014. He recently left Google and is now thinking about how to disconnect devices from the internet using machine learning on microcontrollers or other devices at the edge. By putting machine learning on a sensor, engineers can build devices that don’t need an internet connection for basic tasks.

It’s possible to put sensing such as wake-word detection for limited phrases on a microcontroller. This could enable voice activation for lamps or speakers as needed. We could also enable object recognition in the form of person recognition or rodent recognition on a sensor to build devices such as people counters or rat traps, respectively.

In a research paper written with several others, Warden explains that if we build such smarter sensors, we should also make them incredibly simple, abstracting out much of the current complexity associated with running machine learning on a sensor. He and his fellow authors offer four different use cases including key word detection, object recognition, transcribing numbers or letters from an analog sensor to a digital one, and finger tap recognition. They suggest that such sensors wouldn’t have connectivity, and would have a pre-tested and authenticated ML algorithm loaded on the device ahead of shipment.

Smarter sensors would make it easier for developers to build products using those sensors.  And having the sensor locked down with an established algorithm already embedded on the device would ensure a level of security and accountability for the sensor. Yes, there would be costs associated with this approach, such as the loss of total customization that could potentially reduce the overall cost and and power usage of such a sensor.

However, I do think that cutting out the ML experts and embedded hardware engineers required to design a custom sensor would more than make up for the cost considerations. And if a device took off, then it might make sense to engineer a custom sensor for the workload, much like we see cloud computing companies build their own servers to tweak for any optimal power and performance characteristics.

There is a lot to the paper, and if you are interested in stepping back to rebuild the IoT without some of the layers of complexity and weakness it currently features, I recommend you spend some time reading it. With smarter sensors we can provide a lot of functionality without incurring ongoing cloud costs. We can also create an audit trail for ML algorithms and reduce the surface area to which hackers can get access.

This audit trail, and the testing of such sensors before they get deployed in the field, also offer regulators and academics the chance to test algorithms for bias or unwanted societal effects. For example, it would be much harder for someone who wanted to build a wake-word detection sensor that is keyed to the phrase “abortion” or “baby” to get their algorithm in devices unless they were an expert at machine learning and building embedded systems.

The paper showcases a movement, and a potential business plan for a company that makes sensors according to its principles. I’d like to see such an effort take place, because I don’t believe the benefits of TinyML belong to the few firms with the engineering capabilities to design and implement them. I’d like to see what could be done if such smart sensors were available to everyone.

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Filed Under: Analysis, Featured Tagged With: google, TinyML

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You can have local home automation now for everything except natural language processing and it works just fine with the current generation of sensors. Apple’s HomeKit, Hubitat, Homeseer, Ezlo/Vera, IKEA Tradfri, and most Home Assistant implementations run everything locally except for third-party integrations to cloud-based services like the voice assistants. And of course control when you’re away from home.

I live in an area where the Internet goes out several times a year. We have solar power and run HomeKit as our primary home automation system and rarely even notice as far as the home automation goes. All our motion sensor, contact sensor, light sensor, temperature sensor, and button remote triggered automations still work. You can even get a limited amount of voice control through either local Alexa processing or voice navigation on a tablet.

It’s true that there are some popular home automation systems like smartthings, wink, Insteon, and IFTTT that do require an active Internet connection, but that’s not the only way to do it.

And Matter intends to do everything “local first“ (similar to the HomeKit architecture), which should mean even more devices that can run cloudfree for most people.

Some of the systems do require an Internet connection to get things set up initially, but after that, you don’t need a cloud connection.

Better sensors would be great and I am all in favor of them, but they aren’t a necessity for a cloudfree home automation system.

JD Roberts is correct, there are already ways to run things local. I will add to what he said, why can’t they just make these sensors Z-wave or Zigbee that can already run locally on their own network? Or the (yet to be viable) Matter standard.

This sounds like yet another standard (insert XKCD standards cartoon here), and that is not what is not needed to bring the home automation system to the masses. Matter already is adding confusion and fragmenting an already shrinking market, this new thing isn’t going to make things better.

Apologies if this sounds negative, but it seems like just another way to trap people into another walled garden that doesn’t play nice with existing protocols or hubs. I have been burned one too many times by that, I personally will not buy anything that doesn’t play nice with existing protocols and standards.

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