Both IoT and machine learning are revolutionizing industries worldwide, driving efficiency, business growth and technological advancements. In this guide, you’ll learn the specifics of IoT and machine learning, their unique characteristics in manufacturing contexts, and how they differentiate from each other.
What is the Internet of Things (IoT)?
The Internet of Things refers to a network of interconnected physical objects, commonly known as ‘things’. These objects incorporate sensors and connectivity tools to collect and exchange data over the Internet. IoT has gained prominence in various aspects of everyday life, such as smart homes utilizing energy-saving devices like smart meters, lights, plugs and enhanced security systems like smart doorbells.
In Industry 4.0, IoT is essentially the engine of a smart factory that links all elements of manufacturing processes, such as production insights, customer experiences and employee productivity.
What Industries are IoT Applications Used In?
IoT has been adopted by a wide variety of industries, including:
Additive Manufacturing – Sensors integrated into manufacturing equipment can alert operators about filament replacement requirements or serve as real-time quality control mechanisms. IoT sensors can measure critical factors influencing the end product’s quality, such as temperature, humidity, material flow and printer performance.
Traditional Manufacturing – Similar to additive manufacturing, IoT can be utilized to alert operators when equipment needs to be serviced, materials need changing or if there are any quality control issues.
Healthcare – Wearable healthcare devices utilize IoT software. For example, diabetics can wear an IoT device to monitor their blood sugar levels and alert them about how much insulin to inject.
Logistics – Logistics companies are increasingly reliant on IoT software to make their operations more efficient. Route optimization and fuel consumption can be monitored to achieve quicker transport times.
Energy – IoT technology is present in smart meters and other smart devices, promoting more energy-efficient usage.
Retail – Operations can be vastly improved by the introduction of IoT, alerting staff when products are out of stock and tracking customer behavior.
What is Machine Learning (ML)?
Machine learning is a form of artificial intelligence that enables computers to learn and adapt without explicit instructions. By utilizing algorithms and statistical models, machine learning analyzes patterns and behaviors in data to derive insights and make informed decisions.
What Industries Use Machine Learning?
Machine learning is a growing technology that has been adopted by a number of industries:
Additive Manufacturing – Machine learning has proven instrumental in optimizing additive manufacturing processes. Machine learning techniques are employed to detect potential maintenance requirements in 3D printers, effectively reducing potential downtime.
Healthcare – Machine learning can be used to detect disease through the analysis of medical imagery by learning what diseased and healthy images look like. This has transformed the medical industry as machine learning technology can detect signs of disease not visible to the human eye.
Finance and banking – Machine-based learning can be harnessed by the finance and banking industry to read and interpret patterns in large amounts of financial data, increasing security by identifying fraudulent activity.
Security – Similarly to the banking and finance industry, machine learning can be used to identify large quantities of data. This can include facial recognition technology, predicting the likelihood of cyberattacks or assessing network security.
What’s the Difference Between IoT and Machine Learning?
While the Internet of Things and machine-based learning are two separate concepts, they often intersect and complement each other in various industries.
The IoT focuses on device connectivity and data exchange, whereas machine learning involves developing algorithms that enable computers to learn from data and make predictions without explicit programming.
IoT systems collect and transmit data to centralized platforms or cloud-based systems, while machine learning algorithms utilize the data to make predictions or decisions.
Machine learning models can continuously improve their performance through exposure to historical data or labelled data with known outcomes.
In essence, IoT emphasizes connectivity and data exchange, while machine learning focuses on leveraging data to make intelligent and autonomous decisions.
|
|
Internet of Things |
Machine Learning |
|
Form |
Network of interconnected devices that collect and exchange data through the Internet |
A branch of AI that allows machines to learn from data and improve autonomously |
|
Goal |
Connects physical objects to monitor, control and communicate data seamlessly through devices |
Trains machines to perform specific, repeatable or dangerous tasks with increasing accuracy |
|
Use |
Collects real-time data to monitor environments, automate processes and improve workflows |
Identifies patterns in data to make predictions and decisions |
|
Approach |
Relies on sensors, embedded systems and cloud computing to transmit and manage data |
Uses self-learning algorithms and statistics to build prospective models |
You can also discover the differences between AI and ML, here.
How Will IoT and Machine Learning Affect Business?
IoT and Machine Learning can be utilized together to enhance efficiency and quality control. The IoT technology collects data from multiple sources, and machine learning interprets and identifies patterns in the data in real-time.
What Role Do Humans Have in IoT?
While IoT devices are powerful, they don’t operate in isolation. Behind every connected smart machine are people who design, guide and apply the insights that these systems generate. Human input is essential, not only to set up and interpret IoT data but also to translate findings into real-world actions and strategies. Research even suggests that IoT will under-deliver if companies don’t focus on human-centered design that delivers tangible value.
The COVID-19 pandemic highlighted this interdependence of machines and humans, as IoT acted as a catalyst for Industry 4.0 and accelerated digital transformation worldwide. Businesses adopted IoT more rapidly to align with unprecedented circumstances to optimize supply chains and enable more efficient remote operations – all of which became vital in a more interconnected, globalized economy.
Now, with sustainability regulations directing organizations toward climate-friendly practices, IoT is again at the center of innovation by tracking energy metrics and providing transparent reporting. Yet, the technology itself can’t achieve these goals without skilled individuals. Workforces need talent capable of working with IoT, from engineers and data scientists to strategists and decision-makers who can connect technical insights to business impact.
Looking For Your Next IoT Expert or a Candidate Searching for IoT Roles?
At Alexander Daniels Global, we employ targeted headhunting and direct sourcing techniques to reach both inactive candidates and tap into our extensive network of active candidates. Our specialist team can seamlessly handle your recruitment needs in the additive and advanced manufacturing industry, including IoT recruitment, ensuring you meet the right candidates at the right time.
If you’re a professional in the additive manufacturing industry or advanced manufacturing field, explore our career portal to apply for a range of job vacancies.
To learn more about our services and how we can assist you, get in touch with our team of experts today. We also offer a wealth of HR resources and insights including our annual salary survey to help you stay informed about the latest hiring trends.
If you’re a professional in the additive manufacturing industry or advanced manufacturing field, explore our career portal to apply for a range of job vacancies.
To learn more about our services and how we can assist you, get in touch with our team of experts today. We also offer a wealth of HR resources and insights including our annual salary survey to help you stay informed about the latest hiring trends.
