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5 Industrial IoT Applications that Are Improving Businesses Across Industries

Industrial IoT is a far-ranging field that encompasses almost all IoT technology used in business settings. It’is such a broad category that it can be difficult to find applications that fit your industry and business needs.

Many industrial IoT applications are highly specialized, such as tools that track wildfires and predict their effects on utility companies. In the midst of such specialized technology, it’s easy to forget that there are broader applications that businesses across industries can put in place to improve efficiency and reduce operating costs.

Despite occasionally being overlooked, these apps can reap major benefits for businesses. Here are five industrial IoT apps that are improving results in operations across industries.

1. Video Analytics

Video monitoring has been an important security component of businesses for years. It’s used to monitor warehouses, secure retail stores, and even gain insight on customer behavior. The problem in every situation was processing hundreds or thousands of hours of video footage to find important information.

IoT video analytics is alleviating that issues in multiple industries. Video analytics applications combine machine learning, edge computing, and human analyses to review and prioritize video footage. Video analytics software analyzes video in real-time, sending alerts for security problems as well as providing insight into customers and their behavior.

Unlike human monitors, video analytics software can review thousands of hours of footage without getting tired, flagging only the most important pieces for staff to review. The result is a more accurate system that relieves pressure on employees.

2. M2M Device Management

Everything from connected cars to smart power grids are part of the IoT movement. And many of these devices aren’t just talking to a central command system, they’re also talking to other devices. Machine-to-machine (M2M) device management helps facilitate, monitor, and analyze these connected devices so businesses can capitalize on growth and support the new devices that are entering the market.

M2M device management platforms are largely based around security and control, so organizations know exactly what’s happening in their network. To make this possible, M2M device management applications have multi-tenant architecture that supports hundreds of millions of endpoints on a single instance. They automatically detect devices as they attach to networks, provide automatic notifications, and give you a progressive view of actions, messages, and transactions.

As businesses, cities, and CSPs continue to add connected devices to their networks, M2M device management and communication tools will become even more critical.

3. Asset Intelligence

Closely related to asset management, asset intelligence is an analytics application that uses IoT sensors and connected devices to gather data. Data is compiled into a central system that analyzes it for patterns and important insights.

Machine learning calculates the likelihood and consequence of asset failure and simulates the impact of capital spending strategies so you can perform predictive maintenance and make better business decisions. Asset intelligence helps:

  • Lower operating costs
  • Reduce risk and outages
  • Improve regulatory compliance by analyzing and visualizing asset lifespan and risk

4. Safety Intelligence

Safety can be a major issue for manufacturing and other operations, which is one of the reasons why industrial IoT apps are advancing into this space. Safety Intelligence, another analytics application, helps operations get better insight into your safety programs.

It uses IoT devices and applications to combine data on accident reports, personnel performance, equipment operating data, and weather forecasts into one location. Machine learning and AI process data, flagging safety concerns and highlighting risky situation so businesses can prevent accidents.

5. Business and Operational Analytics

You’ve probably heard it before – with big data comes big problems. As businesses and operations put more systems in place and implement more connected devices, the flood of information increases. None of that information is useful until it can be processed efficiently, with important insights pulled out of the raw data.

Large-scale business and operational analytics application do just that. They enhance your existing systems with powerful tools for assembling data, analytics, and alarms into situational intelligence applications. Developers, business users, analysts, and data scientists all use these wide-ranging tools to create visual analytics applications.

Visual analytics are then used to spot patterns, identify problems, and find areas where businesses can improve operations. The result is more efficient, profitable processes.

Industrial IoT Technology is Adaptable for Different Business Needs

Industrial IoT’s biggest advantage is its adaptability. IoT providers can use many of the same technologies, including machine learning and connected devices, in different ways to solve specialized industry problems or improve overall business results.

The five applications above are a great place for businesses to start improving their operations. Applying these tools in your operation can improve efficiency, lower operating costs, and increase profits. Once you’ve mastered these applications, you can also start looking into other IoT apps that can solve more specific problems.

Which IoT app will revolutionize your operation?

Case Study: IoT is redefining the customer experience. Nokia case study.

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