Internet of Things (IoT) has gained a huge traction due to the ability to gather data from sensors embedded within a variety of IoT devices including Close-circuit cameras, vehicles, smart homes, smart appliances, and many more. Think of IoT as a network of devices which gathers raw and real-time data, analyzes them, and provides desired outputs that benefit the users.
But what after the data is analyzed? What is done with the analyzed report? The data has to be acted upon. Here, Artificial Intelligence can do the needful. AI can get hold of all that data crunched by IoT devices and act on it in a successful and organized manner. Industries that already use IoT devices can automate certain mundane workflows such as documentation, machine maintenance notification alert, and so on when powered by AI.
Intelligent things with AI-backed IoT
The saying, ‘With great power come great responsibilities’, is true for AI powered IoT.AI backed IoT devices can make complex decisions, perform self-learning, and can carry out autonomous decision making.
One can group IoT applications broadly into two categories based on who the end user is, i.e. Industrial IoT for enterprises and consumer IoT for individual consumers. Let’s look into some of the major domains that AI has enhanced.
1. Industrial IoT
Also known as the IIoT, IoT has impacted industries by bringing in unprecedented opportunities. However, it has also brought in a wave of new risks to businesses. IIoT provides the internet with a new ability to control machines, factories and the industrial infrastructure. Some of the characteristics of IIoT include,
- Improved Interoperability where the machines and sensors communicate via IoT
- Availability of Transparent information with the presence of more sensors, which means abundance of information.
- Autonomous decision making now lies in the hands of the IoT devices, where they can detect emergency situations, for instance when a machine servicing is required and can act on it immediately.
Manufacturing is by far the biggest industry affected by the IoT wave. According to a report, ‘global manufacturers will invest $70 billion on IoT solutions in 2020, which is up from the $29 billion they spent in 2015’.Let’s see how some of the processes in manufacturing get a lift with AI enabled IoT:
Detection of machine health using Predictive maintenance : Predictive maintenance involves collection and evaluation of data from machines in order to increase efficiency and optimize the maintenance processes. With predictive maintenance, manufacturers can determine the condition of their equipments and also predict when machines need maintenance.
A startup named Konux, based in Munich, Germany, has developed a machine-learning powered monitoring system for train switches. The Konux switch sensor can be retrofitted onto existing train networks, providing real-time monitoring of track conditions and rolling stock. Data is transmitted wirelessly to the Konux Kora platform, which uses predictive algorithms based on machine learning to alert staff to specific problems as well as drive recommendations for maintenance.
Supply Chain Optimization : With an IoT-optimized supply chain, manufacturers can get hold of real-time data and analyze issues to act upon them before the onset of any major problem. This in turn reduces inventory and capital requirements. In order to track a product, companies have set up smart shelves, which keep a record of when the product has been removed, the total no. of products, and so on. This smart shelf is connected to their entire network which is linked to their planning and demand sensing engine. Here, the AI powered decision support systems help to translate those demand signals into production and order processes.
Read ‘How AI is transforming the manufacturing Industry’ for a more indepth look at AI’s impact on the manufacturing industry.
Adoption of IIoT in retail has upped the game for online retailers. Retail stores now comprise of in-store advertising and gesture walls. These walls help customers search merchandize, offers, and buy products with simple gestures. Retailers also have Automated Checkouts, or most simply self-checkout kiosks. This enables customers to avoid long queues and pay for products using a mobile app based payments system which scans the QR code embedded on the products, contactless payments or other means.
With IoT enabled sensors, retailers can now extract insights about the most popular areas people pass by and where they stop to see the merchandize. Retailers can then send promotional text messages, discount coupons directly on the customer’s phone while they are in the store’s vicinity. For instance, Apple’s iBeacon enables devices to alert apps and websites about customer location. Retailers have also adopted Inventory Optimizations by using digital shelf and RFID techniques for managing their inventories effectively.
IoT in healthcare is proving to be a boon for patients by decreasing costs and reducing multiple visits to doctors. With these healthcare solutions, patient monitoring can be done in real-time. Due to this real-time data, diseases can be treated well in advance before they reach a malignant stage.
These IoT enabled healthcare solutions provide accurate collection of data, automated workflows which are combined with data driven decisions.This cuts down on waste, reducing system costs and most importantly minimizes errors.
Also, creation and management of drugs is a major expenditure in the healthcare industry. With IoT processes and devices, it is possible to manage these costs better. A new generation of “smart pills” is allowing healthcare organizations to ensure that a patient takes his or her medication, while also collecting other vital data.
Next up, we move on to explaining how AI backed IoT can affect and enhance the consumer domain.
2. Consumer IoT
Consumers go for services that provide them with an easy way to do mundane tasks. Let us have a look at some examples where AI has intelligently assisted IoT for consumers benefit.
Connected vehicles are vehicles that use any of a number of different communication technologies to communicate with
- the driver,
- other cars on the road (vehicle-to-vehicle [V2V]): This tech helps wirelessly exchange information about the speed and position of surrounding vehicles. This helps in avoiding crashes, ease traffic congestion, and improve the environment.
- roadside infrastructure (vehicle-to-infrastructure [V2I]): These technologies capture vehicle-generated traffic data wirelessly and provide information such as warnings from the infrastructure to the vehicle that inform the driver of safety, mobility, or environment-related conditions.
- the “Cloud” [V2C]: A Vehicle-to-Cloud infrastructure integrates NaaS (Network As A Service) into the automotive ecosystem and allows provisioning of vehicle-based services for automobile user.
These AI enabled IoT devices and services can automatically respond to preset rules, be remotely accessed and managed by mobile apps or a browser, and send alerts or messages to the user. For instance, Google Home, with a built-in Google Assistant, controls home and helps people with lists, translation, news, music, calendar and much more. Google Home can also answer any questions asked to it. This is because of Google’s huge Knowledge Graph that it is connected to. Similarly, Amazon’s Echo, a voice-controlled speaker and Apple’s homepod also assist in collecting data they get via voice.
The AI can also get all devices within the home connected, with the help of Wi-Fi. With the latest IFTTT technology, your Google Home can talk to Nest and adjust the temperature of your home as per your requirement or the external temperature change.
Health and lifestyle
AI integrated with predictive analytics within the embedded devices such as fitness apps, health trackers, diet planners, and so on, makes them intelligent and personalized. For instance, Fitbit coach app paired with the Fitbit has a huge database. The app uses complex algorithms to extract meaningful information from the user data. This data is further used to recommend highly-tailored workout plans. Also, AthGene, uses ML algorithms to convert genetic information into valuable insights for customizing fitness regimen, diet plans, and lifestyle changes for users.
IoT was only about devices monitoring data and giving insights in real-time. But AI added the efficiency factor, and also gave the power to these systems to take decisions. AI with IoT has a bright future; one can expect smart machines managed via Echo or Google Home in the future.