Streamlining Operations With IoT and Edge Analytics

Data is the currency of modern-day business. It does not matter how much money a business has; if it has its customer’s data, the data can be used to provide enhanced services to the users. Thus, skyrocketing profitability.

With the advent of IoT, today, data is in heaps. The reason for that is the number of IoT devices across the globe which is over 14 billion. This number is expected to rise abruptly, which means more data and more investment to handle it.

The issue of massive data on the cloud or on-premise data store is a huge concern with the increase in the number of devices. This is where the concept of edge analytics comes into the picture. Let’s read ahead and find out how edge analytics can be helpful!

What is Edge Analytics?

The meaning is clearly explained by the word. The term edge signifies the end devices, whereas analytics means analysis of data.

By definition, edge analytics is an approach where data from the end devices, such as sensors, network switches, etc., is collected and analyzed on the device’s location itself. There is no need to send the device data to the central store for analysis.

The use of endpoint devices for data analysis saves a lot of time and computational power, which would otherwise be used in the central location. The use of edge analytics also minimizes the data that needs to be sent to the central data store.

Why Edge Analytics?

As we are clear with the definition of edge analytics, let’s see why you need edge analytics or what its significance is.

One of the most crucial significances of edge analytics is reduced to negligible latency. Let’s take an example!

In the case of an autonomous car or any other vehicle that has smart sensors fitted in it, if it is running at high speed and it is about to hit a barrier or the car in front of it, there is a need for a quick brake. In the case of edge computing, it can be possible as the computation is done on the sensor, but not if the data is sent to the central data store for analysis.

Other than that, there can be scenarios where human safety is a concern, like fire alarms, heavy industrial machinery, etc.

Benefits of Using IoT and Edge Analytics

As we have touched on the benefits of IoT and edge analytics in the above section, let’s uncover more of them!

Real-time Analysis & Decision-making

The key benefit of edge analytics is that data analysis can be done in real-time and in less time. Further, it enhances and speeds up the decision-making process.

Reduced Data Transmission and Storage Costs

The second critical benefit of IoT and edge analytics is controlled data transmission. All the data produced by the sensors is not relevant. Hence, edge devices have algorithms and parameters that neglect irrelevant data. Further, as the data is reduced, the cost of data storage automatically decreases.

Faster Problem Resolution

Edge analytics and IoT can help in faster problem resolution. For example, if the sensors on a telecom tower malfunction, the data can be analyzed on the device, and the nearest service center can be informed of repairs.

Improved Efficiency

As latency decreases significantly with edge analytics, a business organization can repair its faulty products and services quickly and within less time. This consequently enhances efficiency.

Enhanced Customer Experiences

Electronic appliances like refrigerators, air conditioners, and smart cameras come with smart sensors. If any of these device sensors provide odd or abnormal health signals, they can be repaired in minimum time with edge analytics, boosting customer experience.

Use Cases of IoT and Edge Analytics

The combination of IoT and edge analytics can be used in a plethora of industries to boost efficiency, reduce costs, and improve the customer experience. Here are some examples!

Industry	Examples
Manufacturing	IoT and edge analytics are indispensable in monitoring and optimizing production processes. Furthermore, it can also be used to get updates about equipment health. Smart sensors can be fitted in heavy machinery and equipment to capture critical health parameters like water levels, temperature, vibration, etc. Edge analytics can be used by manufacturers to process this data on the equipment location and identify issues. Furthermore, making adjustments to prevent downtime.
Transportation	The transportation sector can gain from IoT and edge analytics in a number of ways! Smart vehicle sensors can capture location, speed, and fuel data to analyze against the ideal values. This analysis can help prevent untimely repairs and accidents and may even improve fuel efficiency. The same data from the vehicles can also be analyzed over time to provide servicing and part replacement for an extended vehicle life.
Retail	The retail industry can leverage the power of IoT and edge analytics in numerous ways. Inventory management and restocking can be done instantly as the sensors can send real-time information about the items on the shelf to the computer. They can also be designed to make a sound when the items are out of stock. IoT sensors fitted in cameras can be used to trigger messages or alerts to customers about available items. These devices can provide alerts based on the user’s location in the store. Store owners can also change the product scenery based on tracking and knowing which product is liked more.
Healthcare	The use of IoT and edge analytics can be a blessing for the healthcare sector. How? Let’s see! Autonomous monitoring of hospital rooms can be done by fitting sensors. Smart sensors like heat sensors can be fitted in the machines and equipment used in the hospital to know about any heating issues. The data can be further used to prevent any system failure. Rather than sending it to the central database, patient data can be analyzed on the device itself. This will ensure faster treatment and care, consequently saving patient life.

Challenges and Considerations

Along with power-packed benefits, IoT and edge analytics also come with some challenges!

Compatible Hardware and Software Issues

As the data needs to be collected and analyzed at the smart sensor itself, it requires specialized hardware and software. The making of special hardware and software takes a lot of time which can be a big challenge for the technology industry.

Data Privacy and Security Concerns

Collecting personal data from users can be tricky as there are certain rules for that. If the data gets hacked, it might be a nightmare for you. Hence, you need to check the rules and regulations related to data collection and its safety.

Tips to Overcome the Challenges!

Though it will take time to set up the entire IoT and edge analytics infrastructure, when designing devices and platforms, keep some key things in mind!

• Powerful security measures: Security measures like strong data encryption, secure authentication, and periodic software updates need to be set in place. This will overcome the data security challenge.

• Trustable Data privacy: Allows the users to check and clarify policies and procedures based on which their personal data is collected and used.
• Compatible with legacy systems: While implementing measures to overcome challenges, keep a check on the existing system. Make sure that your new devices and their respective protocols can be integrated with the existing system.

Wrapping Up!

To offer you a quick review, the need for IoT Technology and Edge Analytics for streamlining operations is necessary. With the increase in user data daily, these two are the only technologies that can enhance and retain the user experience. As there are many criticalities in the implementation of these technologies, it may take some time for the businesses to adapt, but the wave of their usage has started and will surely catch the pace.

If you are planning to develop devices backed by edge analytics while overcoming all the challenges, Intuz is the perfect option for you.