Overview:

The biggest themes at IoT DevCon today in Santa Clara, CA are the following: AI will be pervasive in every industry during at least the next decade; voice is replacing the keypad/keyboard as the preferred human interface, IoT will fulfill its promise and potential once the cyber security and privacy issues have been solved.

As these innovative and cutting edge technologies fuse together experts in the market are forecasting exponential growth over the next seven years while revolutionizing everyday products with amazing potential.

Grand View Research projects the wireless mesh network alone will be worth north of $11 billion globally by the year 2025. One of the significant factors driving market growth is the variety of applications across multiple industries for these platforms, ranging from traditional business projects to emergency services. The inclusion of IoT and AI are expected to expedite the process, allowing for more efficient and effective operations of MESH applications and networks.  AI not only involves massive parallel computing, but also lots of data movement is needed to come up with results.

Here are a few of the IoT DevCon sessions I attended today (please contact the author if you’d like details on any of them):

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Gopher Protocol Inc Decentralized MESH System:

Gopher Protocol, a company specializing in the creation of Internet of Things (IoT) and Artificial Intelligence enabled mobile technologies, today announced that it has completed the first phase of its Decentralized MESH system architectural functionality simulation. These simulations tested Gopher’s unstructured MESH network, performing node and gateway communication scenarios while observing timing and performance. The team was able to successfully simulate “node to node” and “node to gateway” network communication, within a defined range.

From the company’s website:

Gopher Protocol (GOPH) Core Technology is a revolutionary new platform with products that will change the way people interact with technology and each other, because we believe that improving communications will benefit the modern world.

GOPH Microchips communicate via a private, secured protocol and can interact with internal states –  microchips communicate with other microchips –  and external environments – microchips interact with cell phones, mobile apps, computers, tablets, tracking devices and many other digital devices with access to conventional networks (WiFi and Cellular).

Our goal for GopherInsight Microchips is that they will potentially be installed in billions of mobile devices by the year 2020. This will allow GOPH to create its own private communication network, which will enormously benefit the user from behind the scenes. We utilize this private network to improve the computing power, database management, internal memory, and security of mobile devices equipped with GopherInsight Microchips! The potential is enormous and we are constantly developing more advanced features.

A wireless mesh network is a communications network made up of radio nodes (telephones or other connected devices) organized in a mesh topology (random dispersion across a given area). MESH refers to rich interconnection among devices or nodes. Wireless mesh networks typically consist of mesh clients(users) and gateways (internet access points). Other companies that have wireless mesh networks for IoT include Microchip’s MiWi™  (based on IEEE 802.15.4 – low-rate wireless personal area networks or LR-WPANs) and the Wirepas mesh network (based on Low Power Bluetooth).

Above illustration courtesy of Microchip

MiWi supports operation the IEEE 802.15.4 radio PHY in the sub-GHz and 2.4 GHz ISM bands.  Developed to enable low-cost, commercial and smart home networks, MiWi is used in applications such HVAC systems and alarm sensors where reliable self-healing mesh networking is needed.

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The Gopher Decentralized MESH network will be a mobile network, which adds additional complexity as the nodes move frequently. The main challenge of developing Gopher’s MESH network is updating routes of data considering that nodes are moving within the MESH. Managing these nodes is achieved by our time division based electronic hardware combined with Gopher’s Avant! Artificial Intelligence engine that is cognitively learning about the dynamic GEO locations of nodes and gateways in order to control the unstructured mesh network.

“This is a very significant stage for us” stated Danny Rittman, Gopher’s CTO. “We successfully conducted a node hopping simulation which we believe is one of the key technological hurdles in creating a MESH network. In addition, we also performed “node to gateway” communications and multiple “node hopping” all the way to a gateway. The results were successful for a defined range and beyond. We are now constructing testing boards to further analyze the technology in order to identify methods of improvements and advancements.”

“We are also working on our Avant! AI engine, providing it with the mathematical knowledge with the goal of developing it to a point to control the entire system. Unstructured networks are particularly difficult to control without the involvement of highly mathematical models and algorithms” continued Dr. Rittman. Gopher believes the development of a mesh network and technology is crucial to the creation of a communications network that disrupts the incumbent Internet and data providers that are the gatekeepers of communication access for the developed world. Gopher intends to bring connectivity to the hundreds of millions that cannot easily afford the current global cost of connectivity and to make the rapidly growing internet of things more affordable for all.

Read more about GOPH at http://www.marketnewsupdates.com/news/goph.html 

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Other related developments in IoT and AI include:

1.  Microsoft Corporation recently announced a strategic partnership to deliver new technology developments and go-to-market initiatives that accelerate enterprise AI and IoT application development. As part of this partnership, the companies will create a “better together” solution, comprising the C3 IoT Platform™, a low-code, high-productivity PaaS for scaling AI and IoT across enterprises, fully integrated to operate on Microsoft Azure. C3 IoT will leverage Microsoft Azure as a preferred cloud platform and tap into the power of its intelligent capabilities. The companies will conduct co-marketing and co-selling strategies that rapidly scale distribution globally, as well as intensive training for dedicated teams to speed customers’ time to value. Close collaboration between Microsoft and C3 IoT will help enable customers to more rapidly develop and deploy AI-based applications for transformative use cases, such as AI predictive maintenance, dynamic inventory optimization, precision healthcare and CRM.

2. Naveen Rao, vice president and general manager of the Artificial Intelligence Products Group at Intel Corporation said in advance of the company’s upcoming AI DevCon:

This is an exciting week as we gather the brightest minds working with artificial intelligence (AI) at Intel AI DevCon, our inaugural AI developer conference. We recognize that achieving the full promise of AI isn’t something we at Intel can do alone. Rather, we need to address it together as an industry, inclusive of the developer community, academia, the software ecosystem and more. So as I take the stage today, I am excited to do it with so many others throughout the industry.

This includes developers joining us for demonstrations, research and hands-on training. We’re also joined by supporters including Google*, AWS*, Microsoft*, Novartis* and C3 IoT*. It is this breadth of collaboration that will help us collectively empower the community to deliver the hardware and software needed to innovate faster and stay nimble on the many paths to AI. Indeed, as I think about what will help us accelerate the transition to the AI-driven future of computing, it is ensuring we deliver solutions that are both comprehensive and enterprise-scale. This means solutions that offer the largest breadth of compute, with multiple architectures supporting milliwatts to kilowatts.

Enterprise-scale AI also means embracing and extending the tools, open frameworks and infrastructure the industry has already invested in to better enable researchers to perform tasks across the variety of AI workloads. For example, AI developers are increasingly interested in programming directly to open-source frameworks versus a specific product software platform, again allowing development to occur more quickly and efficiently.

Mr. Rao’s AI Devcon 2018 presentation is at:

https://s21.q4cdn.com/600692695/files/doc_presentations/2018/05/AI_Devcon_RAO_Final.pdf