The ever-increasing volume of data generated by digital devices has given rise to innovative solutions like edge computing. Particularly relevant in the field of IoT (Internet of Things), edge computing is not a mere trend, but a technology with potential to revolutionize data processing.

Primarily, edge computing aims to relocate the heavy data processing workload from the cloud to edge devices (like IoT devices). This redistribution enables quicker, real-time data analysis and decision-making than traditional cloud computing methods. Moreover, edge computing does not require centralization of processes, creating a mesh network of local micro data centres for efficient data management. Another emerging term in this context is 'Fog Computing', which essentially bridges the gap between edge devices and the cloud, combining the strengths of both technologies for improved data processing. So, why should businesses consider Edge Computing for their IoT applications? Let's understand the benefits in depth.

1. Edge computing reduces latency - the time required for data processing and analysis. This reduced response time offers significant advantages in situations where even a slight delay can have serious repercussions. A prime example would be in an autonomous vehicle where real-time data analysis can save lives by deploying airbags at the right moment.
2. Cloud computing can pose security, privacy, and legal challenges, particularly for sensitive information. Edge computing solves these problems by processing data near the source, thus preserving data sovereignty regulations and ensuring better control over personal information.
3. Edge computing reduces the burden on internet bandwidth by processing large volumes of data close to the source. For instance, law enforcement agencies could use edge-computing cameras with lower bandwidth to analyze video recordings in real-time.
4. With Edge computing, businesses can secure their sensitive data within their own premises, thus reducing the chances of data breaches. This technology allows security upgrades to be made on edge devices, thus limiting the impact of a potential outage to only the device and its local applications.
5. Unnecessary data transmissions to the cloud by IoT devices not only consume more bandwidth but also inflate the cost of storage and analysis. However, with edge computing, local data acquisition and analysis can be accomplished before sending it to the cloud, thus leading to cost savings.
6. Edge computing decentralizes data processing, thereby reducing the load on the network and ensuring fewer impacts on the system resources when computing IoT devices.
7. Data processing and storage is made more efficient by reducing lag time. Thus, app performance is significantly enhanced.

Edge computing certainly promises to address numerous challenges posed by cloud computing, especially for IoT applications. This evolution towards localized data processing will undoubtedly provide businesses with the competitive advantage they need in our data-driven world.

Here are a few examples of edge computing's significant advantages in various IoT settings:
 

1. Device Management : Edge computing proves vital in managing many device structures and traits. By amending devices to the edge infrastructure, vast functionality expansion and support is achievable for distinct attributes like distributed firmware updates, diagnostics of connected devices and device configuration updates.
2. Priority Messaging : Ever thought about how crucial data gets immediate attention? With edge computing, critical data prioritisation is made possible, stimulating a cascade of actions across multiple devices and applications. From transportation solutions to environmental notifications, health and safety alerts to security actions, priority messaging is at the core of various IoT applications.
3. Data Aggregation : As the number of connected IoT devices increase, so does the data generated by them. Edge computing aggregates this data, promoting network efficiencies, reducing latency and providing richer data sets.
4. Cloud Enablement : The potential advantages that edge computing provides to cloud vendors is phenomenal. By advancing better data storage and processing, higher system reliability is achieved, which also reduces the load on existing data centres.
5. IoT Image and Audio Processing : With the advent of edge IoT, audio, video or image data can be analysed at the source without backhauling the entire data stream. This approach is resourcefully used in many IoT applications like monitoring noise pollution or for security purposes.
6. Healthcare Devices & Security Solutions : In life-saving situations, edge IoT used in health monitors can send instant alerts during emergencies. Furthermore, it's constructive use in security solutions can identify potential risks and alert unusual activity in real-time.
   So, is the introduction of edge computing in Industrial IoT applications beneficial? Absolutely! It offers massive potential gains for mobile operators, customers, and partners. With this technology in play, the dependence on the cloud is reduced, paving way for control over the huge influx of data.

Data processing and analysis speed are indispensable in harnessing the full power of Industrial IoT applications. With time, technology like edge computing will continue to evolve, manifesting its exponential capabilities in various sectors. Embrace this groundbreaking technology and be a part of the rapidly approaching future of IoT.