AI is a key component in optimizing how we interact with our mobile devices and even drive cars for ourselves. In many everyday tasks, we are more likely to come across Machine Learning(ML) algorithms and Natural Language Processing (NLP) methods than we realize.
Two Categories of AI Usage
Two main streams can be used to classify AI's use in improving the functionality of daily life.
Software/Methodology
Voice assistants, image recognition to unlock faces on mobile phones, and ML-based financial fraud detection are some of the most prominent examples of AI software that is used every day. AI software is usually downloaded from an online store. It does not require any peripheral devicesac.
Embodied
AI's hardware side includes its use in self-driven vehicles, drones, robots, and assembly-line robots. This includes the creation of devices that use AI capabilities.
Few Uses of AI Capabilities In Everyday Life
AI- and ML-powered devices and software mimic human thought patterns to enable the digital transformation of society. AI systems can perceive the environment and solve problems. This makes everyday life easier.
These are 10 areas in which AI can help humans meet their daily needs:
Voice assistants
AI-backed Voice User Interfaces (VUI) are used by digital assistants such as Siri, Google Home, Alexa, and Google Home to decipher and process voice commands. These applications can use AI to rely on voice commands and access vast cloud storage databases. These applications can process thousands of lines per second of data to complete tasks and return tailored search engine results.
This technology is seeing a significant shift in consumer awareness. Voice assistant interfaces are quickly improving, particularly in healthcare, where they can be used to diagnose certain diseases using vocal biomarkers. Chatbots based on voice are being integrated into telehealth applications to aid screening and triage.
Entertainment streaming apps
Hulu, Spotify, and Netflix are streaming giants that continuously feed data to machine learning algorithms to improve the user experience.
These streaming apps analyze the interaction of users with different media and recommend customized content. These apps use AI to analyze the increasing amount of user data and create customized content for each user.
AI is also important in uninterrupted streaming. It automates the allocation of servers nearest to the user. The popularity of a media piece affects how bandwidth allocation is made.
Personal Marketing
To increase engagement, brands use AI-driven personalization solutions based on customer data. OneSpot Research found that 88% of consumers surveyed said personalized content makes them feel more positive about a brand.
Personalized marketing via automated email and feedback forms effectively directs consumers to the products they want. This increases their likelihood of making a purchase. AI's recent innovations include computer vision to predict how an advertisement will perform, helping brands reach people most likely to need their products.
AI marketing apps can be used to help prospects or retarget customers, depending on the marketing stage. AI can also help businesses create a logo appealing to their target audience using an online tool. They can use it to learn about their market and how to accurately portray their products/services.
Smart Keyboards
Mobile keyboard apps have been updated to include language detection and auto-correction. This makes them more user-friendly.
These apps can correct errors, switch languages and predict the next word with the aid of AI. AI programmers use the principle of "random forest" to teach these apps how to interpret the context and make precise predictions.
Swiftkey and Typewise now integrate with more than 300 languages and dialects. Recent additions include integrated search engines and real-time translation.
Navigation and Travel
AI programmers behind navigation apps such as Waze and Google Maps never stop working. The ML algorithms that are applied to satellite images can cross-check the vast amounts of geographic data that is being updated every second.
Researchers recently developed a navigation model which tags road features in digital maps. This is done in real-time. These digital maps can also be created simultaneously using satellite imagery, which includes information about parking spots and cycling lanes.
Convolutional Neural Networks and Graph Neural Networks have been used to create imaging algorithms that simplify regular route updates. With the help of predictive models, AI can also be used to determine routes from satellite images that have natural overgrowth.
Read More: How Does Artificial Intelligence Power the Internet of Things
Gamified Treatment
AI has been a part of gaming since the days when classics like Pac-Man and Pong could be used to build intuitive universes. Innovations in gaming AI, however, have tended to present more challenging challenges to gamers and not gauge their mindset.
Gamified apps are being developed to measure the mental fortitude of gamers in the face of certain defeats. This allows gamers to learn how to reduce anxiety and depression.
Some gaming apps offer Cognitive Behavioral Therapy (CBT), which is a virtual reality headset that allows for increased engagement with the user. These games adapt to their users' behavior using AI based on the game's progress.
Auto-driving Vehicles
Global corporate interest is driving large-scale innovation in the technology of Autonomous Vehicles AI. AI is advancing beyond blind-spot detection and cruise control to fully autonomous capabilities.
Deep Reinforcement Learning (DRL), a subset of machine learning, has been used to train autonomous vehicles. Different predictive AI models make it possible to plan your route in the face of dynamic and static obstacles.
Predicting accurately when vehicles around you will swerve or other unforeseen events is possible. Simultaneous Localization and Mapping is the technology that allows for the real-time location of surroundings via sensors.
Facial Recognition Technologies
Face ID unlock the most common use of this technology in flagship smartphones. This technology faces the greatest challenge because of widespread concerns about its use in forensics.
Generative Adversarial Neural Networks reduce error margins in facial recognition software. These neural networks can also be trained to detect the unprofessional use of Deepfake technology.
AI software is also being developed by various industries. It can detect facial expressions and determine mood and intent. Affective computing, also known as emotion AI, is a new area of interest that helps customers evaluate their experience.
Surveillance and Security
It's almost impossible for humans to watch all the CCTV networks at once. It was necessary to automate these surveillance tasks and enhance them with machine learning methods.
AI allows human surveillance personnel to concentrate on the verification and action of critical incidents. AI video surveillance software takes over the constant monitoring and detection portion of surveillance. Artificial intelligence can detect irregular behavior that human eyes might miss.
In surveillance systems for high-risk public places, such as government buildings, an extension of AI-based facial detection software is being used. Liberal governments are looking for ways to minimize privacy breaches through AI surveillance.
Internet of Things
Together, AI and the Internet of Things (IoT) offer a wealth of possibilities for smarter home appliances that need minimal human intervention. The IoT part deals with devices that interact with the internet. However, the AI component helps these devices learn from data.
IoT-enabling involves five main steps: create, communicate, aggregate and analyze, and then act. The effectiveness of the final step, "act," depends on how deep the analysis is. AI adds tons to that.
AI unlocks the potential in the data gathered by IoT devices using sensors. IoT devices can learn from multiple iterations of this data to better respond to human stimuli.
Artificial Intelligence is the Backbone of Technological Progress
AI influences R&D decisions in multiple industries, including healthcare and defense technology. Research shows that more than 65% of globally incorporated companies plan to invest in AI by the end of the next fiscal.
What is the Internet of Things?
The Internet of Things (IoT) is a network of interconnected objects and the technology that enables cloud communication. Thanks to inexpensive computer processors and quick connectivity, billions of people are now online. Today, commonplace gadgets like vacuums and toothbrushes may use sensors to collect data and give users informed responses.
The Internet of Things combines everyday "things" and the internet. Since the 1990s, computer engineers have been adding processors and sensors to everyday objects. The first steps could have been faster due to the large and bulky chips. The early RFID tags were low-power computer chips that might be used to track expensive machinery. These chips became smaller, faster, and smarter as computing devices got smaller.
It is now possible to integrate computing power into small objects at a fraction of the cost. With Alexa voice service capabilities, you can connect MCUs with less than 1MB embedded RAM to enable connectivity, such as light switches. A whole industry is dedicated to IoT devices in our homes, offices, and businesses. These intelligent objects can transmit data automatically to and from the Internet. The Internet of Things is a collective term for all these invisible computing devices and the technology that goes with them.
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What Is The IoT?
An IoT system typically works by real-time data collection and exchange. Three components make up an IoT system:
Smart devices
It is a device with computing capabilities, such as a TV, security camera, or exercise machine. It gathers data from the environment, user inputs, or usage patterns. It transmits it via the internet to its IoT app.
Application of IoT
An IoT app is a set of services and software that combines data from different IoT devices. This application uses machine learning and artificial intelligence (AI) to analyze the data and make informed choices. These decisions are sent back to the IoT device, and the Internet of Things solutions for the device then responds intelligently.
A graphical user interface
A graphical user interface allows you to manage the IoT device or fleet of IoT devices. A mobile app or website can register smart devices and manage them.
What Are Some Examples Of IoT Devices You Can Use?
Let's take a look at some IoT systems currently in use:
Connected cars
There are many options for connecting vehicles to the internet, including cars. You can connect via smart dashcams, an infotainment system, or your vehicle's connected gateway. They monitor driver performance and vehicle health by collecting data from the accelerator, brakes, speedometers, wheels, and fuel tanks. There are many uses for connected cars:
- Monitor rental car fleets for fuel efficiency and cost reduction.
- Parents can track their child's driving habits.
- Notifying family and friends immediately in the event of a crash.
- Predicting and preventing maintenance problems.
Connected Homes
Smart home devices are designed to improve the safety and efficiency of your home, as well as increase home networking. Smart thermostats and smart outlets can monitor electricity consumption. IoT smoke detectors and hydroponic systems can detect tobacco smoke. Home security systems such as door locks, cameras, and water leak detectors can detect and prevent threats and send alerts.
You can use connected devices to your home for:
- Devices not in use automatically turn off.
- Management and maintenance of rental properties.
- You may need keys or wallets.
- Automate daily tasks such as vacuuming and making coffee.
Smart cities
IoT applications make urban planning and maintenance easier. Governments use IoT applications to address infrastructure, health, and environmental problems. IoT applications are available for:
- Measurement of radiation and air quality.
- Smart lighting systems can reduce your energy consumption.
- Monitoring maintenance requirements for critical infrastructures like streets, bridges, or pipelines.
- Profits can be increased by efficient parking management.
Smart buildings
IoT app development improves operational efficiency in commercial buildings and college campuses.
Smart buildings can use IoT devices for:
- Reduce your energy consumption.
- Maintenance costs can be reduced.
- More efficient use of workspaces.
The Benefits of AI-Enabled IoT
The Internet of Things offers a variety of benefits for consumers and businesses, including proactive intervention, customized experiences, and intelligent automation. These are the top commercial benefits of combining these disruptive technologies.
Enhanced Operational Efficiency
AI in IoT analyzes continuous data streams to discover patterns that traditional gauges cannot detect. Machine learning and AI combined can also forecast operational conditions and identify parameters that should be modified to achieve optimal results.
Intelligent IoT can identify redundant or time-consuming procedures and pinpoint which tasks can be optimized to improve efficiency.
Google uses artificial intelligence, for instance, to reduce the cooling costs of its data centers.
Improving Precision Cost
You've probably tried to view data from multiple sheets on your computer. Our minds are limited in our ability to complete different tasks at the same rate. When we're tired, we make more mistakes.
The IoT can break down large quantities of data sent and received by tools. This is the most important aspect of the IoT. Because it is entirely machine- and software-driven, it is possible to complete it without human intervention. This eliminates errors and improves accuracy.
ATM machine withdrawals, online payments, E-commerce transactions and online payments are all susceptible to fraud. You can prevent any money loss by combining the strength of human understanding, IoT Artificial Intelligence, and RPA Artificial Intelligence approaches.
Maintenance & Predictive Evaluation
Anticipating analytics refers to a type of analysis that analyzes data and predicts future events based on those findings. It's not an exaggeration for IoT to say that AI and AI are the basis of predictive maintenance. IoT devices are being used by businesses to alert them of any equipment problems or accidents.
This method, however, will be possible by incorporating an intelligent system. It will allow equipment to perform anticipatory evaluations. This means that the ai development company can predict possibly about the inputs and failures and be able to maintain them.
This reduces the chance of losing money as it is possible to recognize circumstances before they become serious. This will result in substantial cost savings for large corporations and help them avoid business problems.
For example, shipping companies might use anticipation to validate and analyze their data on an ongoing basis to prevent unexpected ship downtimes and maintain their ships through routine maintenance.
Better Client Service and Satisfaction
Every business must be focused on customer satisfaction. Various businesses have earned the reputation for being one of the most customer-centric companies by prioritizing their customers' needs above all else. The human-based customer experience can sometimes fall short due to language barriers and time constraints.
Chatbots are being used to communicate with customers by businesses that recognize the importance of AI. It can offer customers a more personalized experience by collecting large amounts of data. This allows you to respond to their questions and provide them with relevant information.
Higher Scalability
Low-cost sensors and mobile phones are also IoT devices. Low-cost sensors, which generate large amounts of data, are the most common IoT ecosystem. An AI-powered IoT ecosystem analyzes and summarizes data before it sends it from one device to the next. It compresses large amounts of data into manageable sizes and allows IoT devices to connect. This is called scalability.
Read More: When you combine AI and IoT, you get AIoT: A Guide for AIoT
IoT in the Real World
Let's look at the companies that have utilized AI-powered IoT to improve user experience and create new revenue streams.
Robotic Manufacturing
Manufacturing is one industry that has already adopted new technologies like IoT, AI, and facial recognition. Factory robots are getting smarter thanks to sensors embedded in their bodies that allow data exchange. The robots can learn from new data thanks to artificial intelligence systems. This not only saves money but also makes manufacturing more efficient.
Autonomous Vehicles
Tesla's self-driving automobiles are the best example of IoT & AI working together. Artificial intelligence is used to predict pedestrian behavior and card behavior in self-driving cars. They are learning more with each trip.
Retail Analytics
Retail analytics uses many data points from sensors and cameras to track customers' movements and predict when they will arrive at the check-out line. The system can then recommend dynamic staffing levels to reduce checkout times and increase cashier productivity.
Smart Thermostat
Nest's smart thermostat, AI-enabled IoT, is a great example. The smartphone integration can monitor and control the temperature based on users' preferences and work schedules.
What are the business benefits of IoT?
Accelerate innovation
Businesses have access to advanced analytics through the Internet of Things, which can help them uncover new opportunities. Businesses can use customer data to create targeted advertising campaigns.
AI and ML can transform data into insights and actions
Future outcomes can be predicted using historical trends and collected data. For example, warranty information can be combined with IoT data to predict maintenance incidents. This information can be used to provide proactive customer service and build customer loyalty.
Security - Increase
Continuous monitoring of digital infrastructure and physical infrastructure can improve performance, efficiency, and reduce safety hazards. Data from an onsite monitor can be used to combine hardware and firmware version data in order to schedule system updates.
Scale differentiated solutions
Customer satisfaction can be raised with the use of IoT technologies. To avoid product shortages, it is possible to quickly replenish trending products.
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Bottom line
IoT and AI technology can combine to create better solutions and experiences. To get more out of your network and improve your business, you should combine AI with the incoming data from IoT devices.
Using anti-fraud ML models for fraud detection, biometric identification & recognition techniques, and theft & abuse detection methods to protect data, user identity, and physical perimeters, we build Artificial Intelligence solutions that mitigate security risks.
Combining two of the most advanced technologies will result in smart devices that can help businesses make strategic decisions without error. There will be a lot to see and implement. Let's all hope for the best, and make the world more intelligent.
