How AI and IoT are Emerging as the Future of the Industry?

Artificial Intelligence, Internet of Things

The Internet of things (IoT) has a significant potential to fall into the endless pit of a buzzword- vagueness, and it merely is an ecosystem of various kinds of objects that are connected through the Internet. These kinds of objects ranging from cell phones and wearables to machines, generate a constant and massive amount of data every day.   The artificial intelligence (AI) also often falls into the same trap. Particularly with the advent of a new concept, for instance, machine learning, deep learning, genetic algorithms, and many more. 

The goal of artificial intelligence in the new IoT scenario is not only to use the humongous data to extract meaningful insights but also to help IoT integrated setups to derive higher value. 

What are Artificial Intelligence and IoT Technologies?  

It implies the machine’s intelligence, where the device gains the capabilities of simulating a real human brain. Using AI algorithms it enables the machines to learn all by themselves. And with the help of voice recognition, natural language, machine learning, and deep learning subsets of AI technologies, the devices can grasp human speech. Isn’t this amazing? 

The machines can perform the analysis. Big data originated from any source and provided deep insights and also offer predictions based on review with the visual presentations. In Contrast, the Internet of Things application happens when we enable the machine and or any non-computing devices, to connect with the Internet and generate useful data.

Let’s discuss the role of Artificial Intelligence and Internet of Things Technologies 

The role of the Internet in IoT applications is critical as various non-computing devices or components are generating data that are in the form of non-structured data and no SQL formats. It means the computers that are connected with the IoT devices are facing difficulties to use the raw data without further process and can convert them into a useful format.

However, the AI has a subset of various technologies like M2M communication, machine learning, deep learning, natural language processing, and many more. These technologies integrate AI to run an analysis of abstract data.

It was believed that the AI process on the big data is speedy in providing real-time responses to the other connected devices and interface as well where humans can act quickly.

However, the fusion of AI and IoT has turned out to be a success for the organizations in different industries and sectors. Machine Learning, an essential element of AI, gathers all the data using IoT. It also helps:

  • Detect anomalies.
  • Generate predictions.
  • Improve operational efficiency.
  • Reduce downtime, as well as.
  • Enhances risk management .

5 Great Examples of AI-Powered IoT

1: Walmart is using facial recognition system and IoT tags to improve retail

  • As we all know, Walmart is the retail giant, which also uses face recognition technology in its stores to improve and enhance its customer’s shopping experience
  • The images of the customers are captured from the cameras installed in the stores and then fed to the AI.
  • It analyzes the facial expressions of the customers based on the data and identifies their behavior, whether they are satisfied with the products and services offered or frustrated.
  • This helps the staff to deal in the right way with the customers.
  • AI also matches the faces of the people entering the store with a database of suspected shoplifters and criminals. And if a match is found, the notification is sent to the security desk right away. This helps in minimizing the theft from the Walmart stores.
  • The companies built the IoT tags as well for products to help them in stock management, better shelf placements, and check for expiry dates as well.
  • The companies have also built the IoT tags to improve the performances across the retails and warehouses. And these tags also help employees know when to restock items as well as popular monitor trends.

2: Icon to use Intel’s AI-driven technology for remote patient monitoring

  • To extend its remote monitoring capabilities, Icon, a clinical research organization for drug development, has collaborated with intel. 
  • The Icon would be using intel’s Pharma Analytics platform to get better insights regarding drug development and its effect on patients. 
  • The cloud artificial intelligence platforms also capture real-time clinical data offered by sensors and other wearables, as well. It uses smartphone apps as well to collect patient’s information. 
  • The data gathered by this platform is stored in the cloud afterward and analyzed by artificial intelligence and machine learning. 
  • The AI, when coupled with the wearable technology together, helps the Icon to measure the effectiveness of their therapies, therefore, making drug development not only easy but also simple.
  • In the field of remote monitoring, the Intel Pharma Analytics Platform turns out to be a big game-changer by providing a collection of data in real-time. Resulting in the elimination of clinic visits physically and improving the patient’s experience. 

3: Better transit monitoring with AI-powered IoT

  • Transit monitoring is crucial, as well as an essential part of logistics management. The number of technologies like cloud-based GPS, GPRS, GIS, helps to carry out the real-time tracking of the vehicle, this detects the maintenance issues and delays with the trucks. 
  • This data is used to carry out predictive maintenance and help ignore costly repairs. And apart from this, video surveillance technology offers information about traffic and congestion, which is used to plan routes smartly, hence, saving both time and fuel. 
  • With AI, logistics companies are carrying out condition monitoring for trucks to monitor the components like temperature, fuel level, etc. The data which is received from temperature and humidity sensors are installed in the vehicles is fed to the AI, which can detect disasters and provides you with real-time alerts.
  • A large amount of driver data like speed, braking, over speeding, seatbelt usage, and reckless turns are collected on a daily basis with the help of the smart sensors.
  • With the help of machine learning, this data is used to analyze the driving patterns of the individuals, offer proper training, and minimizes the accidents. 

4: CarForce take advantage of industrial AI software for better predictive maintenance

  • The carForce uses the massive amount of data collected by cars’ computers, which otherwise just get discarded. 
  • The goal of the company is to analyze this untapped data and build better predictive maintenance models. 
  • This connected car company offers a small dongle like device which is installed in the car to gather the data generated by the sensors. 
  • The data is then stored in the central repository and used for analytics afterward.
  • Also, the real-time data collected can be used by car maintenance providers to predict failures and mishaps beforehand and carry out timely maintenance. 
  • Apart from this, the data analysis is advantageous specifically for car manufacturers to identify defects and rectify them timely. 

5: Shell saves millions of dollars by tapping the power of IoT and Artificial Intelligence

  • Shell is a big player in the oil and gas industry. In order to make smart and intelligent business decisions, it emphasizes on using the IoT and AI together. 
  • They make use of the digital oilfield solutions. These solutions help them to set up IoT in their plants quickly and enable them to carry data analytics.
  • According to recent reports, the company has saved over a million dollars by applying AI to the data gathered through IoT sensors and monitoring pipelines in their Nigerian oilfields. 
  • The IoT sensors collect real-time information about the different parameters like oil flow, pressure, and temperature. 
  • The information gathered is then fed into an intelligent manufacturing system that analyzes these parameters and displays the suitable temperature and pressure to improve the overall process and derive higher profitability. 

Potential Future Uses for AI-Powered IoT Devices:

The IoT applications help understand the trends as they lay out in the areas where “traction” is proven and the directions where big-companies money already moving. 

1: Security and access devices

When it comes to, IoT applications companies like ACT (Access Control Technologies) are already encouraging the use of critical technologies for unlocking the doors and the use of equipment. Even in organizations consisting of a thousand employees, artificial intelligence is used to determine the regular access patterns and the roles of different employees. Providing insights for future job layouts and potentially detecting suspicious activities. 

2: Emotional analysis, facial recognition

The facial recognition has made some massive leaps and bounds in the last few years alone. So, it is safe to commit that its applications have not been taped till yet. However, companies like Kairos are honed in on marketing apps already, also brandishing the marquee clients like Nike and IBM on their homepage. 

It has probably never been easier, with a camera on nearly every computer and the smartphones made today from the gleaning information from consumer reactions to products and marketing. We could use the example here, i.e., facebook’s auto-tagging that most of the people are familiar with and the other business models. 

AI-enabled IoT Applications in the various industries:

The industrial IoT originally defined IoT as it is used across several industries such as travel and leisure, healthcare, logistics and retail, security, and many other industrial sectors, etc. 

1: Manufacturing Industry

The first is Manufacturing and also the most significant industry from an IoT spending (software, hardware, connectivity, etc.) perspective. IoT is not a new concept in the manufacturing sector. A vast number of manufacturing plants are making use of machine learning as well as the smart sensors in their manufacturing process. In order to optimize the manufacturing process, monitoring, and maintenance of equipment, many manufacturing units are using IoT. The Internet of Things in manufacturing is basically used to track and keep a record of factory assets increase analytics functionality. Moreover, the manufacturing industries are recently working on “smart manufacturing” patterns to enhance and improve the productivity and efficiency of all the manufacturing operations. 

2: Automobile Industry

The automobile industry is also one of those industries that have been benefited after the Introduction of IoT. Self-Driven cars or car GPS systems are some of the magnificent instances of IoT in the automobile industry. IoT integrated automobile companies update the software and respond to real-time mechanical issues by enabling the data communication system. IoT improves vehicles’ performance as well. In addition to it, by using IoT in the automotive industry, we can avoid safety hazards as well as accidents. 

3: Finance Industry

The finance industries and sectors are enjoying the advantages of IoT applications in banking and finance. The IoT has increased security for both the banks as well as for the customers. The Internet of Things has transformed the banking sector in various aspects like mobile banking, ATM, smart cash points, etc. It allows customers with money transfer, cash deposits, and other financial transactions through laptops and especially with smartphones, making it convenient for them over the Internet. 

4: Healthcare Industry:

Healthcare is a vast industry that comprises of numerous stakeholders. IoT is a combination of AI, and these technologies are going to change the entire scenario of the services. Healthcare generates a massive amount of useful data, and IoT, along with wearable, adds in it a significant volume. Also, AI offers profound insights into the data and also assists in HR management, allied pharmacy services, predictions, and suggestions as well. 

5: Travel and Leisure Industry

The Introduction of chatbots is the most common and familiar example of the advent of IoT and AI in the travel and leisure businesses.  AI offers the systems the ability to respond to the customer’s issues and queries without even talking live to travel agents. And AI-enabled IoT provides us the power to dive into things, and streamline processes and transform the whole travel experience. The most common and leading example is London City Airport, the first to use cross-technology networking to enhance the customers’ experience and the running operations in a secure and reliable environment. The IoT devices enable the airline crew to track the journey of the passengers through the terminal, alert boarding gate staff before big queues line up, etc. 

Hence, the AI and the IoT can build an intelligent and integrated relationship management system in the travel and leisure industry. 

6: Retail Industry

The current years have witnessed the retailers of different scales investing in retail tech and innovation to improve their businesses and offer better services to the customers. For example, in the Walmart model, with more than 11,000 brick and mortar outlets, as well as the online stores that meet the sales demand and the customer demand equally and the Walmart, also uses Machine learning, AI, and IoT and the big data to boost the retail performance. It makes the use of facial recognition technology to keep track of customers’ identities,  and shopping patterns enable the IoT tags to monitor product details, employes machine learning skills to optimize the home delivery routes, and also have introduced voice-based search powered by google assistant. In addition to it, with the cross-technology solutions, modern-day retailers can establish a highly engaging and personalized online shopping experience. 

7: Logistics and Transportation Industry

Logistics and transportation is another industrial sector using IoT. For many years, the IoT is taking rounds in warehouses and supply chains. The DHL, global logistics provider, also suggests the AI and IoT applications for logistics optimization. The machine learning and data analytics transform the processes of manufacturing, logistics, transportation, and even the warehousing by making them more productive, efficient, and profitable.  AI and IoT not only limit their operations to backend systems and processes. Transportation firms can use the AI and IoT to proactively respond to the maintenance issues by mitigating costly repairs and downtime, alerting the maintenance staff and keeping the passengers and freight safe. This decreases the costs related to insurance and increases the value of a vehicle’s lifetime. The chances of creating driverless trucks and completely automated truck fleets are not very far.  

8: Security and Surveillance Industry

The physical security industry is the domain that usually craves for technological advancements, but at the same time is slow at technological adoption. However, the customers’ demand, specifically for the physical security systems, is increasing. One another emerging trend in the industry is, to make the product highly adaptable for home and business users, most of the customers prefer a combination of physical and Internet security systems. The integration of human facial recognition systems, including biometric access devices, helps in facilitating remote monitoring of physical security. For instance, Zicom Electronic Security Systems uses IoT to build a platform for electronic surveillance of business premises such as banks, ATMs, and other financial institutions. AI and IoT empower businesses with customized analytics that can be used to create personalized security warnings and ‘trigger’ requirements. 

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To sum up

The AI and IoT empower intelligence and connectivity, and embedded devices make them useful in a wide variety of applications and environments. They are benefiting businesses and industries by offering an opportunity to increase analytics, automation and data processing. “IoT is a pretty tool for organizations of all sizes.” and because of these reasons, it will continue to drive change in the various industries over the next coming decades.