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Did you know that there is an increased demand for artificial intelligence in the IoT market? It is expected to expand at a CAGR of 6.4% in the coming future. Intersection of AI and IoT has become a major topic in the field of technology in the past few years.
AI-powered IoT devices have revolutionized a wide range of industries by enhancing efficiency, improving decision-making, and advancing security and safety, along with providing an extremely personalized experience. Learn about how AI brings innovation in IoT and enhances its features.
Here’s what we’ll cover in the article:
Artificial intelligence is the branch of computer science that incorporates human intelligence in machines to mimic human cognitive activities to perform tasks. Several algorithms and models for machines that require human intelligence, such as decision-making, natural language processing, and image recognition, have been developed.
On the other hand, the Internet of Things (IoT) refers to a network of devices rooted in software, sensors, and other technologies. It generally connects and exchanges information and data with other systems via the Internet. The devices can be simply refrigerators or complex automobiles and machines. Mainly, IoT is used to allow huge amounts of data collection from multiple sources, and its processing and analysis deliver valuable insights and informed decision-making.
Artificial intelligence has become crucial in the IoT ecosystem as it aids in extracting valuable in-depth insights from huge amounts of datasets obtained from several connected devices. AI permits IoT to grasp and adapt to the surroundings and deliver quality decisions based on the learnings without human intervention. In addition, it aids in automating the entire data evaluation process accurately and enhances its efficacy. For example, AI permits proactive maintenance when predicting machine failures. Thus, AI helps in decreasing downtime and enhances overall productivity.
By incorporating AI in IoT, machine learning algorithms aid in finding trends, patterns, and errors of data that cannot be manually detected, allowing businesses to make informed decisions and increase their growth. Numerous technologies pertaining to artificial intelligence can be suited to IoT, such as
a.Machine Learning: Artificial intelligence in machine learning allows machines to learn from data by performing explicit programming. It helps in knowing the updated patterns and trends of the environment to extract valuable insights and make informed decisions or predictions of future events and behavior. It further helps to boost the productivity rate and avoid massive losses.
b.Reinforced Learning: Unlike machine learning, here, machines learn from the feedback from the environment and make informed decisions accordingly. It resolves the optimization issues by interacting with the surroundings and adapting the parameters that enhance productivity and quality. Applications of reinforced learning are autonomous vehicles like Tesla and robotics.
c.Deep Learning: Here, neural networking is widely used to process and evaluate data. It can be implemented in tasks like Natural Language Processing (NLP) and image recognition.
AI, when intersecting with IoT, offers multiple benefits, including
1.Improved Decision Making
AI, when incorporated into IoT, can aid in extracting valuable insights from the huge datasets taken from IoT devices, which helps in making informed decisions. For instance, agriculture data is taken from sensors to optimize crop yield. In addition, in the medical field, a large number of patients’ data are extracted from wearable devices to assess potential health problems and provide necessary treatment to stop making them worse.
By implementing AI in IoT, several regular tasks can be automated. This operation makes the business run more effectively. For example, nowadays, industries are incorporating artificial intelligence to enhance production lines, which further reduces waste and enhances the overall growth of the business.
AI-powered IoT devices are highly recommended for personalization experiences. For instance, in the medical field, artificial intelligence can evaluate a patient's data to deliver personalized treatment procedures.
4.Advanced Security and Safety
AI incorporated into IoT has provided advanced safety and security in many areas. For instance, in the medical field, various equipment are monitored, and problems in instruments can be easily detected to avoid accidents. In cybersecurity, AI evaluates the network traffic and detects potential threats or fraud instantaneously. In addition, in smart cities, AI is incorporated into traffic light sensors and cameras to identify traffic flow.
While implementing AI-powered IoT, several challenges need to be addressed for successful implementation. Some challenges are:
AI-powered IoT is extremely costly, especially for small and medium-level factories. The cost of hardware and software components is challenging to accommodate in low-budget businesses. Moreover, there is a requirement for additional devices for security measures. Therefore, to increase AI-powered IoT usage, it is crucial to identify cost-effective solutions.
It is quite difficult to manage the vast amount of data generated by IoT devices. Integrating AI with IoT requires algorithms to train vast amounts of data and enhance its accuracy. Thus, the management of data and its storage that can be easily accessible and handled by AI algorithms is crucial to processing data accurately.
Numerous manufacturers develop IoT devices with distinct protocols and standards. Incorporating AI algorithms in these devices becomes difficult in different situations, creating interoperability issues while processing data extracted from IoT devices. Therefore, it is crucial to generate common protocols and guidelines to build AI-powered IoT successfully.
Data privacy and security are major concerns for businesses. IoT devices, when incorporated with AI, are frequently deployed in insecure environments, which, in turn, puts them at risk of cyber threats and cyber-attacks. The data generated from IoT devices must be processed with AI in a secure environment to avoid cybercrime. It is crucial to apply powerful security measures to maintain the integrity of the data along with the system.
AI algorithms typically require a significant amount of power to function as they are computationally intensive. On the other hand, IoT devices work on batteries. When intersecting AI and IoT, huge power consumption occurs, which can not be fulfilled by battery-running IoT devices. Therefore, energy-efficient AI algorithms and machine learning must be considered while intersecting AI with IoT devices so that they can properly function on lower power consumption.
Intersecting AI and IoT has opened a world of possibilities for individuals along with businesses. AI algorithms aid in processing large amounts of IoT-generated data, which allows them to make informed decisions and actions instantaneously.
Intersecting AI and IoT can help us track crop yield and decrease waste. AI algorithms in sensors track factors like temperature, the moisture level of soil, soil quality, and others to allow farmers to make informed decisions and optimize their use of fertilizer and irrigation. In addition, potential risks and issues, like disease outbreaks or pest attacks, can also be detected via AI-powered IoT.
AI-powered IoT has revolutionized the medical field by offering personalized care and monitoring patients remotely. Wearable medical devices help us track different health factors based on which informed decisions can be made to avoid making health issues critical.
Sensored AI-incorporated devices have been used by residents and even for commercial purposes. These sensors function based on human activities—for instance, lights in restrooms and temperature adjustments in the room. AI-integrated IoT devices monitor and learn the customer’s preferences and behaviors and act accordingly. It helps in utilizing the energy when needed and saves energy, thus reducing costs.
IoT devices integrated with AI aids in creating smart cities. For instance, sensors in traffic lights assess the traffic flow and adjust the traffic lights accordingly to avoid congestion. Similarly, automated vehicles possess specific algorithms and neural networks to make accurate decisions on the road.
5.Maintenance of Machines
AI aids in predicting failure in the equipment or machines. It helps address the problem in real-time, thus decreasing downtime and maintenance costs. AI analyses data from IoT and allows customers to identify the trends and patterns to take proactive measures to avoid failures or losses.
With the growing need for IoT devices and sensors, AI has been implemented to boost the efficiency of devices and businesses. Yet, there exists a scope of research for developing measures to manufacture AI-powered IoT capable of influencing energy efficiency by finding opportunities to reduce consumption and optimize its usage. It will further aid in saving the cost of individuals and businesses, decreasing carbon emissions, and analyzing industrial settings to eliminate the chance of accidents from machinery and equipment.
With the growing demand for the IoT implemented with AI, the future is expected to have coverage of discoveries and development of new technologies and applications leading to potential services that we cannot imagine today. It will also offer us satisfying benefits while saving our costs, efforts, and time. When IoT devices become more prevalent and AI becomes advanced, innovation in AI-powered IoT will become illimitable.
The incorporation of AI in companies is witnessing significantly increased numbers. It has led to a direct increase in the requirement of experienced individuals capable of handling complex situations. The businesses also require innovative minds that can manufacture, analyze, implement, and optimize the intersection technology of AI and IoT. Are you capable of delivering the requirements?
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Q1. Define the role of IoT and AI in manufacturing.
Manufacturing companies and factories incorporate AI in their IoT to extract information from different units and produce real-time data. It reduces time and effort and enhances efficiency in the process and outcome.
Q2. Is AI better than IoT?
AI and IoT are complementary to each other in performance. However, AI performs and learns from human intelligence, and IoT provides pathways to handle the massive dataset.
Q3. How is IoT related to ML and AI?
IoT collects the data, which is processed through AI algorithms and used for decision-making and prediction through AI.
Q4. Can I combine AI with cybersecurity?
Yes. Artificial intelligence (AI), when combined with cybersecurity, offers potential advantages, including real-time threat detection. In contrast, the traditional threat identification process takes a few hours to a couple of days to find and rectify the threat.
Q5. Is IoT better than embedded systems?
The two concepts are completely different. IoT interconnects the devices over the internet for information exchange. Embedded systems are an integral part of the system concerned with specific tasks.
Q6. Can IoT work without AI?
Yes. IoT can always deliver its task without implementing AI. However, the process and the outcome without incorporating AI will not deliver the potential result that it can provide when powered with AI. With AI, IoT can optimize tasks, predict errors in real-time, analyze huge amounts of data, extract valuable insights, and aid in making informed decisions.
Q7. Does IoT require the Internet?
No, the internet is not mandatory for communication between IoT devices.
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