IoT 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.
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.
Related:- Wireless Network Solutions
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 .
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.