The Internet of Things (IoT) has become a crucial part of manufacturing and business transformation. According to a report from Statista (paywall), the total worldwide volume of IoT endpoints data will reach 79.4 zettabytes by 2025, and their number will approach 75 billion the same year.
Most IoT devices are related to industrial equipment used in manufacturing, healthcare, smart cities, agriculture and utilities. However, the more such systems are scaled, the more acute is the considerations around their deployment and integration with management software.
To reap the benefits and savings from the IoT, we must master proper implementation. So let's look at the points to focus on.
Why Are Industrial IoT Devices So Important?
Enterprise IoT systems combine a set of technologies for running business applications. They connect to physical endpoints, such as technological equipment, healthcare monitors and logistic RFID tags. The data aggregated by devices in the system become invaluable information for making business decisions at all levels.
A proper IoT system helps businesses increase profitability and cost-effectiveness through the following:
• IoT endpoint datasets and real-time analysis with artificial intelligence (AI) and deep learning help proactively and automatically monitor industrial equipment, track performance indicators and detect vulnerabilities. The company can avoid costly repairs and losses associated with faulty machines.
• Improving the quality of processing and analysis of big data helps in determining the best scenarios for the equipment’s work and increases productivity and overall business efficiency.
• Integration of internal data from IoT devices and external information helps optimize supply chains, inventory monitoring, reporting and other essential business operations and can identify cost-reduction sources.
As indicated by the results of a Forbes Insight survey, IoT business transformation increased annual profits up to 5% for 45% of the respondents and 5% to 15% for another 41%. However, with the right approach to integration, these figures can be significantly higher.
Challenges You Can Face During Enterprise IoT Deployment
IoT Device And Data Security
The threat of spyware, data theft and ransomware puts greater emphasis on protecting endpoints. Hackers can even lock doors or gain control remotely over thermostats and electricity in a building.
Therefore, intrusion prevention and detection systems, access control and endpoint and firewall protection must be as innovative as possible. This can take the form of digital certificates and biometrics tools that protect IoT devices at the entrance, network segmentation that ensures unauthorized access blocking, real-time monitoring, virtual patching and other security measures.
IT And OT Alignment
IoT combines information (IT) and operational technologies (OT), but their alignment can be a challenge. IT and OT are often separate departments that don't share workflows and plans. But an IoT enterprise requires close cooperation from these departments, and you need to build a dialogue between them. IT and OT must share values and expectations and jointly define responsibilities, priorities, challenges and budgets.
Maintenance And Scaling
Typical industrial IoT integrations involve thousands of sensors and devices. Each endpoint must be registered and maintained in a central repository that reflects the current deployment’s state. So, scalability and management infrastructure problems are faced by anyone who expands and modernizes this complex system.
You'll want to upgrade the legacy network infrastructure, increase bandwidth and low latency and manage critical app prioritization. That's why the early stages of deployment and integration can be a heavy financial lift, and enterprises must consider their ROI beforehand.
Enterprise IoT Integration: Vital Steps
Preparing And Planning
First, take inventory of all IoT devices in the network. Make sure to keep an up-to-date list of all connected equipment with their details (e.g., manufacturer, model ID, serial number and software versions). It's also essential to determine the risk profile of each endpoint and its behavior as applied to other devices in the network.
Launching A Pilot Project
A pilot project should first be launched based on the results of the preparation and planning. It can then be scaled up to an entire department or enterprise. After the pilot, you should be able to:
• Create a prototype of the platform, considering the integration of all systems and all types of sensors and data formats.
• Determine machine learning models, their integration and retraining opportunities.
• Define the types of dashboards that provide management with the results of analytical data processing.
Collecting, Integrating And Analyzing Data
After launching the pilot project, you can implement a complete technical solution. But connecting endpoints is just the start. The main thing about the IoT is its ability to analyze and process data more efficiently and increase the overall flow flexibility. For this, you need to:
• Organize the initial data collection from disparate sources. You can use edge computing solutions located within the production facility. This will allow you to collect and process data in close to real time and at ultra-low latency, effectively preparing it for deeper analysis via AI and machine learning.
• Analyze the data to generate valuable information. The analytics and AI add-on allow you to get the most out of your IoT investment. Analysis at the network’s edge and center makes it possible to extract all the information from the endpoints, so processing streaming data, self-learning applications and similar tools become a must-have for an enterprise IoT.
• Implement device-to-cloud solutions. These enable peripherals to directly transfer data to cloud platforms and leverage their analysis and visualization tools. Due to the convenience, scalability and cost-effectiveness of edge device-to-cloud computing, it's called the future of IoT.
Technologies based on IoT allow us to extract from production data practical insights that didn't exist before. However, the deployment of IoT systems requires skilled personnel and complex integration of computer systems, software applications, networks and operating systems.
Therefore, it's very helpful to cooperate with an experienced partner company and have a broad vision when developing and implementing IoT solutions. This way, you can overcome bottlenecks in the data flow and gain unprecedented business improvement and transformation.