The combination of Machine Learning and IoT has been a hot topic among people for quite a while now. But this technology in its current state is far from perfect. All its current applications from smart coffee makers to smart wearables have at least one shortcoming common to them. This may not seem like a disadvantage on the first glance but if we ponder about it, this seems clearer. Since we humans follow a very “random” lifestyle, the hard-encoding of smart devices does not seem the logical way. For example, let us assume that on a typical day, I wake up at 8:00 am and I want my coffee exactly 15 minutes after I wake up. But this will be an optimal setting only if I am a disciplined person and I follow my morning schedule to the highest order of strictness. ML will allow these smart devices to be smarter in a literal sense. It can analyze the data generated by the connected devices and get an insight into the human’s behavioral pattern. This will make the devices feel a little bit more like an assistant and a lot less like a liability that has to be encoded.
There are 5 specific features of ML and IoT that will change the way that businesses operations.
1. Build Deeper Customer Relationships
Aren’t just the employees who will benefit from the combination of ML and IoT. It implementing correctly, the right solution can personalize the experience for customers. The days of having to guess what the customers want are over. Many Organizations are using these emerging technologies to gather big data about customers in real-time. This massive influx of data can be harnessed so that businesses can develop products and services that best fit the customer’s needs. Combination of Machine Learning and IOT both play a significant role in this process. In addition to just storing massive data, enterprises can automate the entire process of organizing data so that the customer can receive a rapid response. Data collection and customer interactions reduce the time that workers would normally have to set aside for customer service. This frees them up to focus on larger issues. Even in scenarios where the customer would need to speak to a human worker, machine learning capabilities can be leveraged so that the best possible service representatives are matched with customers based on their unique gender, age, or other demographic.
2. Save Money
The bottom line is that Combination of Machine Learning and IOT can increase your…bottom line. With IT departments under intense pressure to cut costs, a case could be made that these two solutions are true cost savers. For example, in supply chains, ML and IoT can quickly collect and analyze data to determine if a part or procedure has become too expensive to maintain. Early access to the data allows a business to identify cost savings without sacrificing productivity. By identifying cost drivers, an organization can implement changes that lower expenses. Using these emerging technologies empower leaders to reduce unnecessary spending and to optimize business procedures. So many companies are already using both solutions to contextualize and analyze data sets that are retrieved from IoT sensors. In the energy sector, a power utility company can leverage these technologies to determine when a brownout will occur next, and machine learning can automatically raise thermostats in certain homes to prevent the brownout.
3. Increased Operational Efficiency and Productivity
Enterprises that incorporate ML into IoT applications can achieve increased operational efficiency. The machine learning capabilities are able to process data and make predictions in ways that humans are unable to do. The technology is able to calculate large sets of data in a short period of time and offer recommendations about ways that work activities can be more efficient. Productivity inefficiencies will be a thing of the past if more enterprises can leverage the combination of IoT and ML. There are numerous examples in the enterprise of this benefit. ML-powered IoT can help businesses conduct a quicker and smoother hiring process by pinpointing the resumes of the best candidates and contacting them. On supply chains, if an important piece of equipment or part fails, it may take a while for workers to detect that.A combination of Machine Learning and IOT can spot inefficiencies and recommend best practices to improve the process.
This transformation in the manufacturing industry is facilitating the birth of a new concept known as smart factories, which enables businesses to create products more efficiently.
4. Enhanced Security and Safety
Individually, ML and IoT can both improve workplace security. For example, ML can automate the scanning of security footage and IoT can activate gates when an intruder is on the premises. As beneficial as these emerging technologies are by themselves, the combination of both ML and IoT can provide an extra layer of security. By pairing machine learning with machine-to-machine communication, enterprises can predict potential security risks and automate an immediate response. There are some examples of this that are already permeating enterprises. In the banking sector, ATMs are equipped with the capabilities to detect potential fraudulent behaviors and alert law enforcement about criminal activities.
5. These Emerging Technologies Can Save Lives
Finally, ML and IoT can reduce the loss of life around the world, including in the enterprise. As previously mentioned, businesses are using the technologies to make the workplace safer. A great example of this would be with some gas plants relying entirely on IoT and ML for maintenance, because an unmanned plant means fewer potential worker deaths. Outside of the workplace, the solution can also be leveraged to save the lives of clients. When deep neural networks are utilized to analyze the data, medical professionals can accurately predict serious health complications before any symptoms arise.
Advantages
Improving Accuracy Rate
If you have ever tried to analyze data from multiple sheets on your computer, you must have realized that it is a tedious job. Human brains are limited to perform certain tasks at a certain rate, and when the minds are exhausted, we are even more prone to making errors. The Internet of Things has the power to break down large quantities of data coming and going through devices. The best part about this is that since the whole process is machine and software-driven, it can be performed without any human intervention, which makes it error-free and improves accuracy rates.
Predictive Analysis and Maintenance
Predictive analytics is a branch of analysis that looks at existing data, and based on the outcomes, it predicts possible future events. It would not be an exaggeration to say that that IoT and AI are the foundation of predictive maintenance. Nowadays, IoT devices are being used by enterprises to report any mishaps or concerns, like equipment failure, etc., in an automated manner without human intervention. However, by adding Machine Learning, this method will allow machines to perform predictive analysis. Meaning that enterprises will be able to detect possible mishaps and failures in advance and work on their maintenance. Due to this, the chances of losses are decreased highly as conditions are being detected even before failure. This will add up huge benefits in saving costs of big corporations and helping them to avoid setbacks in their business.
Improved Customer Satisfaction
The core of every business is customer satisfaction. Currently, companies like Amazon have earned the badge of being the most customer-centric company by keeping the priorities of their customers before everything else. Companies are recognizing the power of AI by enabling chatbots for interacting with customers. Huge amounts of customer data can be used to provide them with a more personalized experience as per their choices and solving their queries accordingly.
Increased Operational Efficiency
Predictions made through machine learning are highly useful in terms of increasing the operational efficiency of the business. Combined in-depth insights obtained through artificial intelligence can be used to improve the overall business processes from the scratch, which can result in increased operational efficiency and decreased costs. Many companies working on a big scale with airplanes and ships, the insights obtained through artificial intelligence can help them to modify their processes, improve equipment settings, and update inventory on time to save on unnecessary expenses.
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