How IoT is improving processes, interaction, even computer vision

NEW YORK—When a meetup isn’t just a meetup, it’s an actual learning experience. Vaughn Shinall, head of product outreach at Temboo, did more than the usual company profile in his talk by providing the audience with some valuable tips for bringing IoT (Internet of Things) to anyone’s business at the Hardwired meetup last November 16 at WeWork in Chelsea.

Shinall’s Temboo, which offers software stack for IoT applications, gave the following tips:

  1. Start with a small but real, concrete problem
  2. Focus on saving time or money to create real value at the start
  3. Quick wins will help build confidence and expertise for IoT
  4. Get internal backing based on having a working system
  5. See how the data and functionality you’ve created can have additional uses
  6. See how existing applications can be modified for other uses
  7. Build new IoT capabilities on top of existing ones

Providing these tips is essential, as over half of business processes are projected to incorporate IoT by 2020, with about 22 billion IoT devices estimated to be connected already to the internet by 2018.

Shinall showed a factory that has retrofitted its existing operations IoT capabilities to reduce waste. It added automated alerts and sensors to its processes.

It was the modular music studio BLOCKS, however, that was the highlight for the evening for people hearing it for the first time. ROLI, the music tech startup behind it, has raised $43 million from FirstMark Capital. It will reportedly be in all Apple stores globally this holiday season.

The other presenters were Charlie Key, founder and CEO of Losant (IoT solution platform); David Lyman, founder and CEO of BetterView (drone marketplace for aerial photography jobs) and Leif Jentoft, co-Founder of RightHand Robotics (intelligent machines for e-commerce order fulfillment)

Key of Losant talked about real time GPS asset tracking which is expected to grow, as sensors, GPS units and cellular modems have become readily available.  About 38 billion devices are equipped with tracking capabilities. As such, many now see the value of tracking the location and health of nearly everything, including shipments.

The actual devices used will rely on cost, physical size, environmental conditions, geographical location and many more. Losant provides systems integrators and product manufacturers with the flexibility to choose and connect to any hardware using any communication method on any network. Its application services and additional platform capabilities cover remote asset management, GPS tracking and mapping, reporting and M2M data integration.  Understanding GPS data natively to visualize locations and geofence the information is crucial.

How does it make money? “People pay us based on data points,” explaining that the compay “works with companies with physical assets like tow trucks.”

As a platform for capturing and analyzing drone data, Lyman of BetterView claimed that they have software that makes it easy to capture data.  It reportedly combines drone-gathered, expert-analyzed imagery with public data like assessor’s permit, fire station proximity, and historical weather to pinpoint risks, estimate costs, and drive action around buildings and properties.

Founded two years ago, BetterView combines public data, drone imagery and computer vision plus human experts to analyze data to its 70 customers. It claims to have a 3,500 pilot network, analyzed, 4,200 rooftops or the equivalent of 130 million square feet.

Lyman said if you’re too early (in the drone space), you can get burned. If it holds its promise, he estimates the industry to rake in 1.8 million sales in by 2020. “We see adoption in commercial business.”

Already, drones and AI are improving insight and transforming how we interact with the physical world.

Another presenter, RightHand Robotics provides end-to-end solutions that reduce the cost of e-commerce order-fulfillment of electronics, apparel, grocery, pharmaceuticals, and countless other industries.

How would you like images automatically tagged? Clarifai does it

NEW YORK—Last July 18, HUI Central featured Clarifai, the three-year old artificial intelligence company that focuses on visual recognition and solving real-world problems for businesses and developers in its midtown East office.

What problems? Imagine having hundreds of images but tagging each one of them on your site? That would be too much of a chore. Clarifai does the tagging for you when you upload them—automatically.

Presenter Cassidy Williams showed Clarifai’s powerful image and video recognition technology, built on machine learning systems and made available to developers via a clean API. Williams showed how the technology works using “convolution neural networks.” It reportedly improves its image recognition capability with consistent use.

Williams compared convolution to adjacent by saying the former is fast to train and can find multiple items whereas the latter offers no recognition of special structure but is good for finding a single item. Both, she said, creates a multilayer neural network.

What are convolution neutral networks? Deeplearning.net defines it “as biologically-inspired variants of MLPs. From Hubel and Wiesel’s early work on the cat’s visual cortex, the visual cortex contains a complex arrangement of cells. These cells are sensitive to small sub-regions of the visual field, called a receptive field. The sub-regions are tiled to cover the entire visual field. These cells act as local filters over the input space and are well-suited to exploit the strong spatially local correlation present in natural images.

“Additionally, two basic cell types have been identified: Simple cells respond maximally to specific edge-like patterns within their receptive field. Complex cells have larger receptive fields and are locally invariant to the exact position of the pattern.

The animal visual cortex being the most powerful visual processing system in existence, it seems natural to emulate its behavior. Hence, many neurally-inspired models can be found in the literature.”

Today, big companies are confident how deep learning can handle large data sets plus have greater computing power. It’s a game changer for AI prototyping. Not only that, it can serve as a boon for advertisers trying to pinpoint better use and even best timing for any use of photo or videos.

Clarifai has both a REST API that could be integrated with your preferred language along with a Python, Java and Node.js API. For more info, visit developer.clarifai.com or github.com/clarifai