Artificial Intelligence and the Internet of Things Techs, Together at Last


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All IoT devices would require intelligent coordination and control. In the last decade, spectacular strides were made in AI systems, to work in coordination with IoT, regardless of their differences.

AI seems to be the favorite topic in today’s press releases. There is plenty of talk, plenty of implied fear, and even more misunderstanding and confusion about exactly is AI and what it is not. AI is impacting current and future states of the world. It’s not going away and is likely to be even more relevant as it matures. In general, AI is defined as computerized systems, which appear to mimic human cognitive functions.

The IoT refers essentially to an ecosystem of discrete computing devices that have sensors connected via the internet infrastructure. The concept could have been bubbling away in the industry for some time, but democratization of computing technology via affordability and availability of small computing devices now pushed if firmly to the mainstream. In essence, Iota is about computing power being agile, decentralized and mobile, freed from confines of the office and home.


In the past decade, the IoT evolved from being a futuristic business buzzword, which most people understood only vaguely, into a cutting edge business strategy, to practically status quo. Worldwide spending on the IoT could reach $772.5 billion this year, a fifteen percent increase from last year. Much of the spending would come from organizations. Sixty-six percent of executives now integrate IoT into their operating models.

By applying artificial intelligence to IoT, forward-thinking leaders optimize processes, acquiring new insights from all interconnected things, allowing new services, boosting customer relationship and making ‘cognitive’ engines, which could reason and interact more naturally with humans than traditional digital systems.


AI and IoT have different histories, but are in the same places in their evolution. Both started with focus on boosting legacy systems. For the internet of things, this means automating and enhancing existing processes and infrastructure for better productivity as well as efficiency. For artificial intelligence, the initial apps were focused on boosting existing human-centered processes. These days, the move is going forward to an integrated IoT-native and AI-native approach, designed from the ground up for transformative digital methods. In most instances, new IoT solutions have in-built AI capabilities from the beginning.

The convergence spurred a pioneering rush of new solutions, disrupting norms, but also building opportunities for new business models, new work roles as well as new value propositions. Some examples include the following.

1. AI and IoT enable automation that is disrupting the labor market by making a demand for new and different set of skills in a lot of industries. In the United States, the industries transformed most by the changing roles are manufacturing, accommodation and food services, transportation, agriculture, warehousing, mining and retail.
2. AI and IoT drives the move in a lot of industries form product to service-oriented business models. IoT provides business leaders data that they could use to make intelligent trade-offs. AI provides the intelligence required to make the choices.
3. AI and IoT build new value propositions. Take the example of SLAM or Simultaneous Localization and Mapping in drones. SLAM enables drones to understand unknown surroundings in a literal way on the fly, even in obstacle-filled, dark environments far beyond the reach of GPS or the internet. With SLAM, drones could fly to dangerous situations, like buildings damaged by natural disaster or fire, to check for people trapped or hurt. With in-built real-time machine learning into IoT devices, SLAM has become one of the most relevant drone apps in security, safety and surveillance.


Why is the explosion of new AI and IoT developments happening at present? There are some interesting differences that emerge.
The internet of things has been around for some time in niche apps. Nevertheless, it came into light only a few years ago when three things occurred:

  • Lines of businesses emerged as key tech buying centers, breaking away tech solutions from the exclusive domain of IT and shifting focus to solving relevant business concerns.
  • Traditional markets, like transportation and manufacturing saw accelerated transition of business structures away from custom, closed, vertically integrated, single-vendor approaches to open systems with best-of-breed elements from numerous vendors that form modern and cost-effective solutions.
  • Need for multi-vendor interoperability as well as better cost structures that drove the adoption of open standards.

Unlike the internet of things, the AI emergence was driven more by technology revolution than business evolution. Deep learning capabilities have accelerated recently, in part enabled by availability of more and more powerful hardware. AI, in the process has also become more important to business, powered by a surge of real-time data, which comes from IoT systems.
As architectures and use cases mature, AI implementations are expected to follow the IoT path and be more decentralized as well. If logic is set already, AI-based systems like predicative maintenance could be deployed in specialized fog nodes that run on FPGAs or even ASICs eventually. The fog implementations dramatically would reduce costs and complexity of AI and IoT based solutions, accelerating the adoption and business impact.


In the IoT world, the utility staff could see how many devices are connected to the system, and then react to avert a brownout, for instance, by turning the thermostat up to three degrees. An in-built AI could alert utility staff to impending brownout, which requires human action in order to avert. Or AI could be more sophisticated and turn thermostats proactively up to three degrees at homes and non-essential business, while keeping thermostats stable at facilities that are temperature-sensitive, like refrigerated warehouses and of course hospitals.

Applied artificial intelligence is when things begin to get interesting in the IoT. Intelligent IoT no longer is a concept of the future. It’s happening today, at this very moment, but only at around 5 percent of organizations. These days, it’s a competitive edge. Also, it’s a big opportunity for anyone else who could catch up.

Ritesh Mehta
Ritesh Mehta works as a senior Technical Account Manager in a software development company named TatvaSoft Australia based in Melbourne. He specializes in Agile Scrum methodology, Marketing Ops (MRM) application development, Android app development, SAAS & SOA application development, Offshore & Vendor team management. Also, he is knowledgeable and well-experienced in conducting business analysis, product development, team management and client relationship management.


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