Machine learning and IoT are one of the topmost trending topics. According to the study, you will witness more than 55 billion IoT devices. Moreover, Machine learning has been adopted by the top organizations for their IoT platforms, including Microsoft Azure, Google Cloud IoT edge, and Amazon AWS IoT. This blog post will cover enough information on Machine learning with IoT, including market size, benefits, and industry use cases.
Machine learning was introduced in 1959 by an inventor named Arthur Samuel, working with IBM. Machine learning is part of Artificial Intelligence, which is mainly used to analyze the data with AI’s help and identify patterns and make decisions with less human interference.
Machine learning plays an important role in data science by providing statistical methods and algorithm prediction. Also, it helps in knowing the key insights of data mining projects. These key sights help make quick and correct business and application development decisions.
The Internet of Things (IoT) refers to devices connected to the internet that collect and share data. With the help of cost-effective chips and the wireless network, it becomes easy to create products that can be considered in IoT. These IoT devices have received immense growth after the innovation of sensors added to objects to get more digital intelligence. The IoT (Internet of Things) has made the world more responsive and smarter by integrating the digital and physical world altogether.
The machine learning field is growing rapidly, along with IoT. Small cameras and other IoT components are now easily available on mobile devices, computers, traffic control systems, parking systems, and home appliances. Millions of IoT devices are manufactured worldwide that collect a variety of data kept in the machines through the internet, allowing machines to understand more precisely that data and make them more useful in a simple way.
Till 2021, Machine learning has a market size of 15.66 Billion USD, which is expected to go upto 21 Billion USD in 2022. According to Fortune Business Insights, the market size of Machine learning will grow immensely upto 209 Billion USD with a CAGR report of 38.8%.
According to IoT Analytics, the enterprise IoT market size has grown upto 157.9 Billion USD with a CAGR of 22.4%, which is expected to expand upto 525 Billion USD by 2027. North America is the fastest-growing market in the field of IoT.
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After understanding Machine learning and IoT, let’s understand the advantages of using IoT and Machine learning in business operations.
Machine learning and IoT help automate the daily task that occurs in businesses. IoT devices help access more precise data that helps get work done more efficiently in less time. Business process automation (BPA), with the help of Machine learning and IoT, business process automation (BPA) brings more productivity to businesses that reach upto 40%. The automation facility helps streamline the work and helps other workers in the organization focus on other value-adding tasks.
IoT and Machine learning help in improving the operational efficiency of businesses by reducing waste. IoT sensors provide the details of resources that are not useful for business, and here Machine learning presents analyze data with the help of algorithms.
Machine learning algorithms and IoT reduce the inefficiency and help get different alternative procedures that reduce the waste.
The implementation of IoT has provided the most favorable support in supply chain management. The IoT sensors used in vehicles and shipping containers provide critical details such as the quality of products and real-time data. The data brings visibility to the supply chain. However, the combination of IoT and Machine learning provides more scalability to your business. Machine learning uses the real-time data generated by IoT devices, predicts disturbances that might occur, and warns to manage accordingly.
The combination of Machine learning and IoT reduces the potential security and safety issues quickly with the help of the sensors and devices. The combination provides a secure ecosystem that helps organizations manage and predict the risk factors that include financial, cyber, and many others.
Today, IoT and Machine learning are used in various sectors, including manufacturing, agriculture, healthcare, etc. Do check out the below list of industry-wise use cases of Machine learning with IoT.
In terms of human activities, Agriculture is considered as the most fundamental activity. According to a report, overall world food production must increase by 70% by 2050 to keep pace with the global demands. The agriculture industry is expecting the usage of Machine learning and IoT rapidly, as the number of connected devices is 70 Million, which will increase a lot in the coming years.
In the modern agricultural era, the interaction between the farmer and the agriculture process is all done with the help of data generated from the combination of Machine learning and IoT.
Healthcare sectors have started using technologies that help fulfill the healthcare facility, in-house diagnostics facility, and disease prediction tools built with IoT and Machine learning. IoT provides all types of medical devices, including wearable devices and monitoring tools for patients to give heads-ups to patients and doctors.
Whereas, Machine learning offers technology to get medical records and integrated data extracted with the help of IoT. Interesting, right? Suppose you are in the same sector and looking to hire Python developers with expertise in IoT and ML to turn your unique healthcare project idea into reality, then you are on the right path to success for your organization.
IoT and Machine learning in the manufacturing industry have provided great impact by helping in enterprise resource management, maintenance, and automated industrial processes.
Enterprise resource management revolves around resource management, supply chain management, work management, and health and safety initiatives. Businesses gather real-time data from the resources (asset) with the help of IoT sensors.
Business owners rapidly adapt the smart resource management system to encounter problems by providing real-time solutions to enterprises.
The few common benefits of Machine learning with IoT in enterprise asset management include a highly responsive environment (ecosystem) and an increment in operational efficiency.
Machine learning with IoT detects the maintenance problems and alerts the concerned team to solve the problem accordingly, and this technology saves a lot of workforce and time. This technology schedules the maintenance cycle of the machine depending upon the usage. Machine learning and IoT saves unnecessary maintenance costs.
IoT and Machine learning provide full potential growth to businesses, and these technologies are helping businesses become more efficient and bringing more scalability. Machine learning and the Internet of Things are reshaping the business world. Machine learning is transforming businesses. Therefore, it is right to use both technologies in your business and choose the best company to implement AI & ML services along with the Internet of Things in your organization.
Yes, it is required to have Machine learning for IoT. Whenever an IoT system brings dependency on humans, it fails. Therefore, it becomes necessary to support machine learning to avoid errors and smooth the process.
Machine learning is relevant and useful for cloud computing and IoT because it helps rectify and solve the problem before the users within the system.
One of the major benefits of using IoT and Machine learning in organizations is providing real-time data, data analytics, threat alert, and cyber-attack detection.
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