Useful Tips to Improve Your IIoT Deployments


The Internet of Things has become a buzzword in the industries as it has the power to transform businesses. IoT has immense potential of creating new business models and has prospects of huge financial returns and operational improvements. As such the Industrial Internet of Things (IIoT) is gaining momentum and the manufacturing industry is leading in the adoption rate. 

Numerous companies and industries have already deployed data-harvesting sensors and analytics platforms for turning raw data into better business outcomes. Thus, the Industrial Internet of Things (IIoT) has made a shift from a buzzword to a business priority. Though IIoT presents numerous benefits, it also comes with some challenges for organizations that fail to properly plan and execute the strategy. This is because any change in the existing operating practices poses some challenges and IIoT also involves changing business processes and need people with advanced skills. 

As workplaces have become increasingly digitized, IoT is likely to keep growing. However, to avoid network pitfalls, there are some strategies that can help in successful networked deployments. Though every deployment is unique, still by avoiding some mistakes and adopting a few key practices, you can ensure successful IIoT deployment. 

Look into the Analytics

As the number of IIoT devices in industrial control systems rises, the volume of data also increases significantly that industrial companies need to manage efficiently. It is a good practice to condition raw data into contextualized data, preferably at the source. Edge computing is also gaining the attention of many companies and industries. In order to prevent data overload, a scalable analytics approach is useful as it solves the problems that exist at different levels of your enterprise. To improve operational productivity, enterprise-level analytics can integrate plant-floor information with business intelligence. While for the purpose of optimizing machines, processes and plants, it is better to implement machine-level or plant-level analytics in edge devices such as controllers and plant-floor servers. 

Tighten up your Security 

Security is the biggest IIoT challenge faced by the industries. The advancing technology is also vulnerable to security threats when data is easily accessible to both malicious and non-malicious threats. In order to prevent security threats, it is important to follow a holistic approach in line with best industry practices for protecting intellectual property and other assets. This includes conducting a security assessment to identify risk areas and potential threats. After identifying the potential risks, mitigation techniques should be implemented. It is recommended to adopt a defense-in-depth (DiD) security approach which makes use of physical, electronic and procedural safeguards to create multiple layers of protection throughout your enterprise. Moreover, always work with trusted vendors only and install industrial firewalls in addition to other practices to implement secure IoT systems.

Customize with experts  

Some technologically savvy companies take a DIY approach of developing a data-harvesting infrastructure in-house. Though this might appear affordable and a fully customizable option but only for simple pilots or single control systems.  A full-scale IIoT deployment requires experts with knowledge of developing algorithms, artificial intelligence, and predictive-analytics applications.

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