Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
How AI is Changing IoT?
Over the past few decades, the business world has seen steady adoption of the Internet of Things (IoT). The next wave of IoT evolution is upon us as advances in Artificial Intelligence (AI) and Machine Learning(ML) unleash the possibilities of IoT devices utilizing “Artificial Intelligence of Things,” or AIoT.
AIoT − A Game-Changer for Consumers, Businesses, Economies, and Industries Adopting and investing in AIoT will enable consumers, companies, economies, and industries to take use of its capabilities and gain competitive advantages.
Why IoT Needs AI?
IoT enables devices to talk to one another and act on these discoveries. It makes things difficult for businesses. Businesses are having trouble effectively processing the data & using it for practical decision-making and insights as IoT use rises. Data transfer and the cloud are two major issues.
The bandwidth required to transfer data from IoT devices to the cloud is constrained, and the cloud cannot scale proportionately to handle all the data that arrives from IoT devices. IoT device data collection generates latency and congestion regardless of the size and sophistication of the communications network.
Let’s see some examples to understand need of AI in IoT −
Autonomous vehicles are only one example of an IoT application that depends on quick, in-the-moment decisions. Autonomous vehicles need to analyze data and make quick judgments to be efficient and secure. (just like a human being). Latency, inconsistent connectivity, and inadequate bandwidth cannot be a barrier for them.
There are several IoT applications other than autonomous automobiles that depend on this quick decision-making. IoT devices are already used in manufacturing, and delays or latency could affect the procedures or restrict capabilities in an emergency.
Biometrics are frequently employed in security to limit or permit access to particular regions. Without quick data processing, there may be lags that affect performance and speed, not to mention the dangers in emergencies. High security and extremely low latency are required for these applications. As a result, processing must be carried out at the edge. Data transfer from a local system to the cloud and back is not practical.
Benefits of AIoT
For businesses, AIoT offers a host of advantages that help them realize the full potential of their data. Here are a few of the most important advantages of AIoT.
Preventing Downtime
Downtime is a problem for some businesses, such as offshore oil and gas. Downtime from unexpected equipment failure can be quite expensive.
Operational Efficiency Boosting
IoT devices generate enormous amounts of data, and AI can evaluate and identify underlying patterns much more quickly than humans. AIoT can improve overall operational efficiency by anticipating operational circumstances and the adjustments required for better results.
Making New and Better Products and Services Possible
As natural language processing advances, it becomes easier for humans and machines to converse. By enabling improved data processing & analytics, AIoT can improve new or existing goods and services.
Enhancing Risk Management
To adjust to a market environment that is rapidly changing, risk management is required. AI and IoT may use data to prioritize the best course of action and foresee dangers, enhancing employee safety, reducing cyber threats, and reducing financial losses.
Key Industrial Applications for AIoT
Predictive Maintenance − AIoT can be used to predict equipment failure before it happens, allowing companies to perform maintenance before a failure occurs, minimizing downtime and repair costs.
Quality Control − AIoT can be used to monitor and control product quality during the manufacturing process, ensuring that products meet specifications and reducing waste.
Supply Chain Management − AIoT can be used to monitor and optimize the supply chain, reducing lead times, improving delivery times, and reducing costs.
Smart Energy Management − AIoT can be used to optimize energy consumption by automatically adjusting lighting, heating, and cooling systems based on occupancy and environmental conditions.
Intelligent Transportation − AIoT can be used to optimize transportation routes, reduce congestion, and improve safety by monitoring traffic patterns and adjusting traffic signals in real time.
Agriculture and Farming − AIoT can be used to monitor and optimize crop growth, soil conditions, and weather patterns, allowing farmers to maximize yield and reduce waste.
Healthcare − AIoT can be used to monitor patient health and detect potential health issues before they become serious, allowing for early intervention and improved outcomes.
Conclusion
In conclusion, AIoT is a game-changer. It brings revolution for consumers, businesses, economies & industries. While IoT devices collect vast amounts of data, AI can analyze it and simulate smart behavior to support real-world decision-making processes with minimal human intervention.
AIoT offers huge benefits for organizations. It includes sidestepping downtime, improving operating efficiency, encouraging new & improved products and services, and improving risk management. Key industrial applications for AIoT include predictive maintenance, quality control, supply chain management, smart energy management, intelligent transportation, agriculture and farming, and healthcare. As AI & IoT continue to evolve, AIoT will play an increasingly vital role in shaping the future of business & technology.
199 Views
