thebaldgeek

Most of us are not really involved in designing or building new electronics hardware, but we all use it. Daily.
It’s worth taking a moment then to look at what’s happening in the hardware world and see what changes are in store for us…… And most likely, in store for us this year!

http://radar.oreilly.com/2014/12/hardware-start-ups-now-look-a-lot-like-software-start-ups.html

Joichi Ito is the director of the MIT Media Lab. Ito, who is also co-chair of the O’Reilly Solid Conference, recalls sending a group of MIT students to Shenzhen so they could see for themselves how manufacturing is evolving. “Once they got their heads around the processes in a deep way, they understood the huge differences between prototyping and manufacturing. Design for prototyping and design for manufacturing are fundamentally different,” says Ito. The problem in today’s world, according to Ito, is that “we have abstracted industrial design to the point where we think that we can just throw designs over a wall” and somehow they will magically reappear as finished products.

Just hang on a sec here…. MIT students, from USA, went to China to learn about manufacturing…… That right there speaks volumes… Moving along…
There is a difference between prototyping and manufacturing. Stop here for another second…. This is something that I have had to learn here at Opto.
I’m a mashup guy. I can throw stuff together, sometimes quickly, sometimes over months of work, but either way, it’s very much a prototype. Its a kluge.
A bunch of shoddy code and hardware all stuck together with duct tape.
Sometimes, I can’t even reproduce what I have done! It’s working, I can see it, test it, demo it, but even I can’t make another one…..
Manufacture it in volume. Uh, not so much.
It’s been pretty cool and interesting (if at times personally frustrating) to learn how to step back and see how to take an idea and actually MAKE it into a product that can be sold and used by customers the world over.

The existing paradigm — the status quo — favors companies whose products and services are based mainly on software because software can be scaled rapidly at minimal cost. The emerging paradigm favors companies whose products and services are based mainly on hardware because the cost of developing and manufacturing hardware is dropping precipitously.

Here is the key that I wanted to get to.
The line between hardware and software is blurring.
As end users we are going to see this shift in the products we buy and use.
And sadly, in the products we throw away. (Just a personal note on that one, I really really miss my circle of mates back home, we had a nice system of passing ‘old’ hardware around – it got used and reused, it got hacked and re built many times – over here, it gets thrown out and I never get my grubby paws on it!).
Hardware is getting cheaper, we are not going to have to save and save for the new shiny, it will be affordable enough that we don’t have to take months to consider buying it. It also means that the upgrade cycle will become faster.

The innovators in places like Shenzhen are showing the world that hardware start-ups can look a lot like software start-ups. They don’t necessarily need tons of seed money or venture capital; they can be spun up relatively quickly; and if they fail, they can be broken down and sold for spare parts. That’s the paradigm shift — and the people who control large portions of the global economy and decide where to invest trillions of dollars, yen, yuan, won, or rupees are beginning to see hardware as the coolest new shiny object.

It will start to happen this year. It will no longer take 2-3 years from when a new prototype is paraded in the press till we can buy it.
That time is going to become 4-6 months.

Hardware looks like the new software.

To me this is a massive missed opportunity.
These guys have gone to a lot of trouble to snatch defeat from the jaws of victory.

http://www.inversepath.com/usbarmory.html

It’s a little expensive, but such an interesting idea. Build a small Linux computer. A really small one. Powered by a USB port is a great idea as well.
Its just that they have put zero methods of connecting it to it other than the USB port…….

The USB armory hardware is supported by standard software environments and requires very little customization effort. In fact vanilla Linux kernels and standard distributions run seamlessly on the tiny USB armory board.

Freescale i.MX53 ARM® Cortex™-A8 800Mhz, 512MB DDR3 RAM

USB host powered (<500 mA) device with compact form factor (65 x 19 x 6 mm)

ARM® TrustZone®, secure boot + storage + RAM

microSD card slot

5-pin breakout header with GPIOs and UART

customizable LED, including secure mode detection

excellent native support (Android, Debian, Ubuntu, FreeBSD)

USB device emulation (CDC Ethernet, mass storage, HID, etc.)

Open Hardware & Software

If they had thrown, at the very very very least, Bluetooth on there, then there would be a bunch of real world uses for such a little computer.
Of course, as soon as you add one feature, someone else wants another and so on, but my point is, I just do not understand who goes to so much effort to build said device these days and does not include a single connectivity option. (USB is NOT a connection option – You need a computer to talk to a computer for that…..)

Shame. But there are so many other options out there, we simply can shrug and move on.

(The point of this blog entry, in case you missed it, is just to point out yet another Single Board Computer (SBC)).

This one is for my mate Dan.

Rogers Communications today (Dec 2nd 2014) announced a funding commitment of approximately $4 million to Wavefront to accelerate the growth of machine-to-machine (M2M), the Internet of Things (IoT) and wireless businesses in Canada.

Rogers is like the Telstra/Verizon of the great white north.
They are a service provider of all things communications.

Granted, 4 million bucks is not exactly a lot of money, I suspect it’s more a case of they are dipping their toes into the IoT pool to see how it goes before jumping in, but hey, it’s a start.

Nice wrap up article that is easy to read;

http://radar.oreilly.com/2014/12/cheap-sensors-fast-networks-and-distributed-computing.html

The trifecta of cheap sensors, fast networks, and distributing computing are changing how we work with data. But making sense of all that data takes help, which is arriving in the form of machine learning.

They spend the first half of the article talking about how ‘computing’ has swung like a pendulum from cental based (think mainframe computers) to distributed (think PC’s talking to a central server).

They are saying that we are now fully at the edge. Both cell phones, tablets and PC’s have got lighter and thus further away from the central servers than ever before.
This is largely due to the ubiquity of Wifi. Most places we go have network connectivity. Our cell phones and smart devices can ‘phone home’ almost anywhere we go.
Each app can reach it’s mother ship and can do its function with very little intervention from the user.

There’s a renewed interest in computing at the edges — Cisco calls it “fog computing”: small, local clouds that combine tiny sensors with more powerful local computing — and this may move much of the work out to the device or the local network again.

Systems architects understand well the tension between putting everything at the core, and making the edges more important. Centralization gives us power, makes managing changes consistent and easy, and cuts on costly latency and networking; distribution gives us more compelling user experiences, better protection against central outages or catastrophic failures, and a tiered hierarchy of processing that can scale better.

It’s this edge computing or ‘fog computing’ that I am really interested in at the moment.
Both in new sensors, but also in existing sensors.
There is just such a huge installed base of sensors and data that is not tapped into, that is not really getting much attention in the whole IoT hype.
This existing base of data is ripe for the picking….. There is no need to spend a lot of time or money tapping into it either… With ‘just a few lines of code’ we can expose this data to AI and deeper analysis.
It can come with very little work since it’s just a matter of exposing it.
I feel that by pushing this edge data to a central server can be done in a secure way (by pushing the data, no outside code (ie, hacker) can reach in and affect the process) and without impacting on the smooth running of the existing process.
As a first step, lets get the data uploaded. Get it stored and start the AI process. Once clear trends or trouble shots are identified, then we can look at how best to the correction sent back down to the process.

I’m really excited for the cheaper, faster, lighter aspects of new IoT devices, but hope that we don’t forget about the installations that have been installed and running for 10+ years.