Image the IOT application case with the help of AI in the near future

 

The Internet of Things is the network of smart devices like phones, computers, vehicles, home appliances, etc. which are embedded with sensors, software, actuators, and connectivity which makes communication possible between the devices. Communication between devices is in the form of exchange of data, or it can also be conversational. This helps in integrating our devices of daily use into the computer-based world so that we may control them through computers. It results in more efficient processes, reduced human intervention and economic benefits. IoT is a popular topic these days. It is predicted that by 2020, there will be 30 million IoT devices in the world. AI, or Artificial Intelligence, is the intelligence demonstrated by machines. It tries to imitate the natural intelligence of humans, which means it mimics the cognitive functions that humans perform using their mind such as learning and problem-solving. Both of the above-mentioned technologies are getting popular, with many companies already adopting them and investing to make it a part of their products and processes. While AI makes the machines learn from their experiences and data, IoT is about devices interacting using the internet. Currently, many IoT devices are connected with each other and are generating roughly 3.5 quintillion bytes of data on a daily basis. This data is a powerhouse of information. It can be used to make predictive models, do analysis, and create a smart world around us by helping machines learn.

 

Machine learning helps in reading, interpreting, and utilising such heaps of data. Machine learning aids the development of artificial intelligence in machines, that can help them act cognitively for our benefit. Through this combination of artificial intelligence and the internet of things, we can teach decision making to machines. Hence, empowered machines will act as smart assistants for us. These smart assistants could be devices like Alexa telling the devices in a smart house what to do. For example, a smart home will be managed by a smart assistant device which manages the devices at home. So, whenever the refrigerator runs out of milk, the smart assistant will get the information through the IoT sensors on the refrigerator communicating through internet connectivity between devices. The smart assistant will then place an order to the nearest grocery store. The store will receive the order and fulfil it by sending a drone or a robot with the grocery. The payment will be handled automatically through connected online wallets. This is a classic example of a personal smart assistant enriching human lives by using the combined power of IoT and AI. Similarly, in the field of B2B technology, recently IBM launched the Watson Assistant, a smart enterprise assistant that is fuelled by the combined power of IoT and AI. With the usage of the cloud, it uses IoT and AI to do wonders for businesses. It can be accessed via text or voice mode and tries to help businesses increase their brand loyalty and transform customer experiences while keeping customer data secure. The assistant is pre-trained for many industries like hospitality, customer care, banking, etc. It is not limited to listening to personal commands but also delivers proactive and personalised services to the customers. An existing example of the Watson Assistant is ‘Josie Pepper’, an assistant at the Munich Airport’s Terminal 2 which acts as an ambassador to assist passengers. It has a rich conversational back-end covering a range of topics, from weather information to small talk. The Royal Bank of Scotland is already piloting the Watson Assistant to act as a triage call centre by responding to customer queries or directing to a human agent as required. IoT devices cannot function without artificial intelligence, and artificial intelligence, in turn, needs IoT devices to be of greater use for humankind. It has a wide range of use cases from personal usage to optimising enterprise operations. Together, both these technologies hold the power to transform our lives.

 

 

Benefits of Using IoT and AI Together

The Internet of Intelligent Things makes IoT applications realize their full potential. Artificial intelligence and machine learning bring more detailed data insights to the table at a faster pace. Enterprises are looking forward to making use of IoIT to reap the following benefits:

 

Improving Accuracy Rate

If you have ever tried to analyze data from multiple sheets on your computer, you must have realized that it is a tedious job. Human brains are limited to perform certain tasks at a certain rate, and when the minds are exhausted, we are even more prone to making errors.

 

The Internet of Intelligent Things has the power to break down large quantities of data coming and going through devices. The best part about this is that since the whole process is machine and software-driven, it can be performed without any human intervention, which makes it error-free and improves accuracy rates.

 

For example, ATM withdrawals, online payments, and e-commerce transactions are prone to high risks of fraudulent activities. With the combined power of human understanding and IoT machine learning and RPA techniques of artificial intelligence, potential frauds can be taken into account in advance, thus preventing any loss of money.

 

Predictive Analysis and Maintenance

Predictive analytics refers to a branch of analysis that looks at existing data, and based on the outcomes, it predicts possible future events. It would not be an exaggeration to say that that IoT and AI are the foundation of predictive maintenance. Currently, IoT devices are being used by enterprises to report any mishaps or concerns, like equipment failure, etc., in an automated manner without human intervention.

 

However, by adding artificial intelligence, this method will allow machines to perform predictive analysis. Meaning that enterprises will be able to detect possible mishaps and failures in advance and work on their maintenance. Due to this, the chances of losses are decreased highly as conditions are being detected even before failure. This will add up huge benefits in saving costs of big corporations and helping them to avoid setbacks in their business.

 

For example, shipping companies can use predictive analysis to check and analyse their data timely to avoid any sudden downtime of a ship and keep maintaining their ships through regular servicing from time to time.

 

Improved Customer Satisfaction

The core of every business is customer satisfaction. Currently, companies like Amazon have earned the badge of being the most customer-centric company by keeping the priorities of their customers before everything else. However, human-based customer experience fails at certain times due to several factors such as language barriers, time constraints, etc.

 

Companies are recognizing the power of AI by enabling chatbots for interacting with customers. Huge amounts of customer data can be used to provide them with a more personalized experience as per their choices and solving their queries accordingly.

 

Increased Operational Efficiency

Predictions made through artificial intelligence are highly useful in terms of increasing the operational efficiency of the business. Combined in-depth insights obtained through artificial intelligence can be used to improve the overall business processes from the scratch, which can result in increased operational efficiency and decreased costs.

 

With precise predictions, you can get insights about time- and cost-consuming tasks in your business and automate them to increase efficiency levels. Moreover, for companies working on a big scale with airplanes and ships, the insights obtained through artificial intelligence can help them to modify their processes, improve equipment settings, and update inventory on time to save on unnecessary expenses.

 

 

Combining AI and the Internet of Things, Three Real World Use-Cases

 

The example applications that I’ve outlined below are all in use today, and have been chosen as representative examples of a broader trajectory of applications. I aimed to avoid overly niche applications of IoT, (like the “connected pacifier” or the “tray that alerts you when you’re out of eggs”) or IoT applications that don’t involve AI in any form. The following AI and IoT combinations are useful examples of how these two broad concepts collide.

 

It’s important to note that many so-called “IoT” devices wouldn’t make this list. By the criterion we’re selecting for (connected devices that leverage artificial intelligence), a device isn’t “smart” merely by virtue of being controllable via an iPhone app. Below are some useful examples:

 

1 – Automated vacuum cleaners, like that of the iRobot Roomba

 

iRobot set the standard with it’s first commercially successful automated vacuum in 2002. Founded by MIT roboticist, the company has developed technology to help it’s puck-shaped vacuum robots to map and “remember” a home layout, adapt to different surfaces or new items, clean a room with the most efficient movement pattern, and dock itself to recharge it’s batteries.

 

While the artificial intelligence applications in the Roomba aren’t as celebrated as broad consumer AI advances such as Facebook’s facial recognition or Apple’s Siri, it is nonetheless the industry standard in it’s class, and a clear example of artificial intelligence “embodied” in a robot (which you can now control on your app, see Roomba’s latest promotional video for the 980 model).

 

2 – Smart thermostat solutions, like that of Nest Labs

 

Though the “smart home” hasn’t exactly revolutionized life for most of us, some companies are ardently aiming to change that – and there’s few better examples than Nest, the company acquired by Google for a reported $3.2 billion.

 

As an IoT device, Nest’s clean digital interface is (for many) a welcome change from the clunkier physical dial, and it’s smartphone integration allow for temperature checking and controls from anywhere. This is “IoT” in principle, but many claim that Nest’s look, feel, and interface made the device more inviting and simple to use (aided largely by the fact that Nest’s founders were influential Apple employees, involved in the development of the iPod and iPad).

 

In terms of artificial intelligence application, Nest’s device “learns” the regular temperature preferences of it’s users, and also adapts to the work schedule of it’s users by turning down energy use. This AI application is certainly novel, but it’s pragmatic benefit (home comfort, potentially serious reduction of energy use) and effective marketing could be said to be the biggest factors behind it’s sales success (an estimated 100,000 sales per month in January 2014).

 

3 – Self-driving vehicles, such as that of Tesla Motors

 

Cars are “things,” and insomuch as we’re interested in “things” that leverage powerful artificial intelligence, automotive technology is ahead of the curve (pun intended, I suppose). This isn’t necessarily because autonomous vehicles will be the easiest IoT innovation to bring to life (with legal and ethical concerns, the jury is out on how long it’ll take to have driverless highways anytime soon), but with nearly all major car manufacturers throwing billions of dollars at the problem, it certainly has momentum (pun intended, I suppose).

 

To use Tesla’s technology as an example, we’ll need to understand how Tesla’s autonomous vehicle technology really works. An article in Fortune refers to Tesla CEO Elon Musk’s response to the question of what makes Tesla’s self-driving cards unique: “The whole Tesla fleet operates as a network. When one car learns something, they all learn it. That is beyond what other car companies are doing…”

 

Interestingly enough, Google’s self-driving approach isn’t all that different, and employs machine learning (and many hundreds of thousands of road-miles of test data) to predict the behavior of cars and pedestrians in various circumstances.

 

 

Potential Future Uses for AI-Powered IoT Devices

 

Today’s IoT applications are useful in understanding trends, as they lay out areas in which “traction” is proven and directions where big-company and venture money is already moving. However, autos and vacuums account for the tip of proverbial iceberg of potential IoT+ AI applications:

 

1 – Security and access devices

 

In terms of purely IoT applications, companies like ACT (Access Control Technologies) are already furthering the use of key fob technologies for unlocking doors and uses of equipment. Even in organizations with well under a thousand employees, artificial intelligence could be used to determine regular access patterns of different employees or roles and tiers of employees – providing insight for future office layouts, and potentially detecting suspicious activity (using the same kind of technology that modern cybersecurity uses in detecting outliers).

 

Though we weren’t able to find key fob / access key technologies integrating artificial intelligence or predictive analytics, we would suppose that as fob technology and adoption improve, this area may be rife with security insight (particularly for larger firms assessing data across many locations).

 

2 – Emotional analysis, facial recognition

 

Facial recognition has made some massive leaps and bounds in the last five years alone, and from surveillance to marketing, it seems safe to say that it’s applications haven’t been tapped. Companies like Kairos are honed in on marketing applications already, brandishing marquee clients like Nike and IMB on their homepage.

 

With a camera on nearly every computer and smartphone made today, gleaning information from consumer reactions to products and marketing has probably never been easier. Facebook’s auto-tagging is an example that most people will be familiar with – and other business models and uses are still to be fleshed out. The Washington Post (among other publications) has written about the potential social and ethical implications of ubiquitous facial recognition technology.