The IIoT Revolution: What’s Next for Manufacturing in 2025
As a facility manager or systems engineer, it’s tough to truly “punch out” at the end of the day. A busted pipe, failing motor, electrical issue, or any number of concerns can strike when you’re off-site and threaten disaster. Disaster or not, each failure brings safety risks and costly slowdowns. But with the Industrial Internet of Things (IIoT), you can monitor and manage your facility remotely to keep everything running smoothly, even when you’re not there in person.
The IIoT market is poised to hit $1 trillion globally by 2030, fuelled by edge computing, 5G expansion, and AI/ML integration. The combination of these technologies unlocks powerful insights, business intelligence, and preventative maintenance. But, for many facilities still using legacy equipment, not everything is equipped to serve smart data.
Is it time to invest in all new equipment? Or can you retrofit “dumb devices” to future-proof your operations?
What is the Industrial Internet of Things (IIoT)?
The Industrial Internet of Things (IIoT) is the technology that enables advanced analytics and insights pulled from manufacturing processes and equipment. It leverages advanced software and applications, coupled with smart industrial components that communicate with the online ecosystem, including:
Smart sensors: Advanced sensors that monitor real-time metrics such as temperature, voltage, vibration, humidity, and even the movement of personnel across a facility.
IoT actuators: Intelligent components that control physical movements—like opening valves, rotating shafts, or adjusting pressure—with precision. They also track operational data such as cycles, torque, and runtime.
Human-Machine Interfaces (HMI): Intuitive dashboards that allow operators to visualize and control equipment status remotely. Integration with AR (augmented reality) or voice interfaces is growing in adoption.
Edge devices: Computing units that process data locally at the source before sending relevant insights to the cloud. This reduces latency, cuts bandwidth costs, and allows real-time decision-making even with intermittent connectivity.
Industrial gateways: Protocol translators and security buffers between legacy systems and modern IoT networks, ensuring seamless communication across disparate equipment and cloud platforms.
Condition monitoring systems: Integrated systems that use sensors to track vibrations, acoustics and thermal signatures to analyse and assess equipment health, and flag issues.
Asset tracking & RTLS (Real-Time Location Systems): Monitor the location and status of tools, materials, and vehicles within facilities and across supply chains.
AI-powered analytics platforms: Machine learning models now analyze massive volumes of IIoT data to uncover inefficiencies, detect anomalies, and suggest optimizations.
The above is only a sampling of the many pieces of equipment and technology that make the IIoT and smart factories possible. Keep in mind that there are numerous unique software platforms, apps, and devices that power the IIoT, and newer manufacturing devices that already come with smart capabilities out of the box.
6 benefits of investing in IIoT
The IIoT comes with a number of benefits, which vary depending on your industry and the kinds of equipment you work with. Despite these variables, there are several core benefits that apply to most situations.
1. Improved operational efficiency and productivity
IIoT devices provide real-time visibility into performance and workflow efficiency. Smart insights help to identify ineffective or obsolete processes, so you can continuously assess the efficiency of operations.
With this information, it’s easier to make targeted adjustments, measure the impact instantly, and continue fine-tuning elements for maximum workflow efficiency.
Over time, these capabilities also help optimize resource allocation, shorten production cycles, and increase overall equipment effectiveness (OEE), which significantly boost productivity and even sustainability.
2. Predictive maintenance and failure prevention
Analyzing usage patterns, asset performance, and historical service data helps to proactively identify low-impact maintenance windows for equipment. This removes the challenge of determining the optimal maintenance schedule for equipment and avoids unnecessary maintenance interventions or unplanned downtime.
Predictive monitoring not only helps to optimize equipment maintenance, but it also allows you to turn off equipment before it fails completely.
For example, say you have a motor that’s overheating but no way to monitor the temperature. Typically, you wouldn’t know it’s overheating until a scheduled check, or worse, a visual indication like smoke or total failure of the motor. With smart sensors, you can see and be alerted to the temperature rising before it hits a critical threshold and take remediation steps.
3. Enhanced safety through real-time monitoring and alerts
Equipment or machine failure can cost you production time and revenue, but more importantly–it can cost human lives. Fortunately, Industrial IoT devices can help you prevent catastrophic failure and improve worker safety.
With real-time monitoring of devices and automated alerts, you can properly turn off equipment before disaster strikes. Incidents involving being struck by objects or equipment are one of the leading causes of workplace injury, so it’s important you do everything you can to prevent this from happening.
4. Data-driven insights for informed decision-making
The IIoT takes out the guesswork, allowing you to make data-driven business decisions. This is because IIoT can provide data on the following, and more:
Data on the environment, such as air quality and moisture
Behavioral data, including which machines are used when, and which paths are taken most often
Total outputs for equipment and lines
Energy usage, both across the org and per device
Automation performance, from outputs to downtime
With the above information, you can make more informed decisions around which equipment to upgrade, if pathways and workflows are optimized, potential maintenance costs, and more.
5. Greater flexibility and adaptability in production processes
In the pre-Industrial Internet of Things days, it was virtually impossible to check on equipment and manufacturing locations without actually being there. (Save a phone call with maintenance or management.)
The IIoT makes it possible for your team to see how equipment is performing, what maintenance needs are on the horizon, which locations are running smoothly, and more — no matter where you are.
IIoT also allows you to pivot quicker. When you have access to vast data and insights, you can see issues before they spiral and react faster, map out new workflows, and ultimately adapt to anything thrown at you.
6. Automation and smart manufacturing
Integrating sensors, smart actuators, connected equipment, and IIoT platforms lays the groundwork for automation of manual workflows and industrial processes.
Robotics is increasingly becoming a core component of this shift—automated systems such as robotic arms, inspection drones, and automated guided vehicles (AGVs) are now commonly used to carry out repetitive or high-risk tasks with precision and consistency.
Accurate planning for smart automation systems is critical. AI-driven robotics relies on precise environmental mapping to navigate tasks. Capturing a facility with a digital twin provides an accurate spatial reference that teams can use to plan sensor placement, simulate automated pathways, and ensure that robotics systems integrate smoothly with existing infrastructure. This helps prevent unplanned downtime, speeds up commissioning, and improves long-term system reliability.
Together, these technologies enable smarter manufacturing environments where automation is data-driven and spatially aware.
Top emerging IIOT trends in 2025
The Industrial Internet of Things isn’t new, but it’s changing rapidly. In 2025 and beyond, there are a number of trends you can expect to see take hold.
Pairing digital twins with IIoT technologies
As organizations push for remote accessibility, digital twin platforms have a larger and more important role. Digital twins facilitate manufacturing processes by making it possible to virtually visit any space regardless of location. Coupled with IIoT data, users can access analytics and real-time equipment performance in a virtual environment.
Beyond just visual access, digital twins add essential context to IIoT systems. Without them, teams are often left interpreting raw data in spreadsheets—numbers tied to sensor labels with little to no spatial or visual reference. Rarely do IoT data feeds include images or detailed environmental context, making it harder to diagnose issues or understand anomalies. With a digital twin, users can visually correlate sensor data with the actual layout, equipment placement, and surrounding conditions. This makes it easier to identify potential causes of inefficiency or variance.
Widespread adoption of 5G and private networks
5G’s low latency and high bandwidth are unlocking new use cases for IIoT–especially in environments where fast, reliable communication is critical, such as autonomous vehicles, remote robotics, and real-time video analytics. Meanwhile, private 5G and LTE networks are gaining traction in industrial settings for secure, localized connectivity.
More edge computing applications
Edge computing advances make it possible to do more data processing locally, rather than via cloud computing. But it’s moving beyond simple data filtering to support real-time analytics and AI processing. This will allow for even faster results, and more ownership of data and business intelligence–especially in bandwidth-constrained or remote environments.
Artificial intelligence integrations
Advanced AI and machine learning will continue to make inroads in IIoT devices and platforms, allowing equipment and beyond to learn as it goes: analyzing sensor data, detecting anomalies, and continuously optimizing processes. From dynamic energy management to predictive quality control, machine learning is shifting IIoT from reactive to proactive.
Cybersecurity for IIoT systems
As IIoT networks expand, so does the threat surface. In 2025, there is a growing emphasis on built-in cybersecurity measures, including zero-trust architectures, anomaly detection at the edge, and secure device onboarding to protect critical infrastructure from evolving threats.
Interoperability and open standards
Vendors and industries are prioritizing interoperability to break down data silos and promote the modernization of “dumb devices”. Adoption of open protocols and standards like OPC UA, MQTT, and DDS is rising, allowing IIoT systems to integrate across vendors and legacy equipment more easily.
Real-world applications of the Industrial Internet of Things (IIoT)
The Industrial Internet of Things has a number of real-world applications, from helping digitize operations to streamlining production lines.
Digitizing manufacturing operations
The IIoT, coupled with digital twin technology, makes it possible to truly digitize manufacturing operations. While IIoT delivers real-time data on equipment performance, environmental conditions, and system status, that data often exists in silos—spreadsheets, dashboards, or disconnected systems with little context. A digital twin brings that data to life by placing it within a spatially accurate 3D representation of the physical environment.
At Siemens, the global manufacturing powerhouse, the integration of these technologies came to life when they used Matterport’s Digital Twin platform to capture and faithfully recreate their spaces virtually. Using the Matterport SDK (software development kit), they embedded real-time IIoT sensor data directly into their virtual tours–linking metrics like temperature, humidity, machine uptime and energy use to their exact physical locations.
This spatial context helped Siemens’ global teams identify inefficiencies, detect anomalies, and better understand how equipment performance was affected by its surroundings—all without needing to be on site.
With the help of Matterport’s Measurement tool, the team could even verify space and equipment measurements and dimensions remotely via the digital twin. Executives from Siemens were able to perform comprehensive reviews of various locations and analyze assembly processes in great detail — without everyone cramming into the same physical space.
By anchoring real-time data in a shared, visual model, Siemens eliminated miscommunication across its global operations—creating faster, more informed decision-making at scale.
Predictive maintenance
Maintenance is inevitable, but costly breakdowns aren’t. With the right approach, you can fix issues before they escalate, saving time, money, and stress.
Using IIoT-connected devices, you can monitor the heat of equipment, get accurate usage statistics to determine wear and tear, and more. All of this information can help you predict when something might need maintenance, especially when compared to maintenance records from other equipment.
In the past, you’d only know about a failure as it happened. With real-time data collection, you can respond faster and pull the plug on dangerous incidents before disaster strikes.
To make this information even more actionable, sensor-driven data points can be attached to their relevant locations using annotations in a digital twin. Readings like temperature or pressure can be pinned to the exact component, providing a clear, spatial context for the data. This lets remote teams triage issues more effectively, addressing concerns before they escalate into downtime.
Additionally, AWS integration ensures that digital twins are quickly accessible for teams to collaborate on faster inspections in the cloud. By combining IIoT data with spatially accurate digital twins, maintenance shifts from reactive to proactive.
Streamlining process optimization
Information is power, especially when it comes to manufacturing and process optimization. IIoT-connected devices provide rich data that not only help you optimize processes but also streamline how those optimizations are designed and implemented.
Embedding IIoT data in digital twins enables remote teams to collaborate effectively on process improvements. Cross-functional groups can:
Run virtual inspections combining spatial context and live IIoT data
Experiment with new workflows or equipment layouts in the digital space before making physical changes
Identify bottlenecks or safety risks by visualizing data in relation to the actual facility layout
Accelerate design iterations by reviewing and tweaking processes remotely, reducing downtime and speeding up implementation
Taking on these challenges in an immersive environment removes the need for frequent travel, reducing costs and speeding up design iterations.
Learn from Forrester how you can quickly react to change in the manufacturing world.
Risks and challenges associated with IIoT
While IIoT exists to largely make your life easier, this doesn’t mean there aren’t risks and challenges in this space.
Security
Like any connected device, IIoT-powered ones are vulnerable to hacking and other online security threats. Cybersecurity risks for IIoT devices are twofold, in that breaches can occur externally via a network, or internally via an employee.
The good news is that there are steps you can take to strengthen your IIoT security.
Make sure your network is well protected and that all outgoing data is encrypted. This makes it more difficult for any external threat to get your data.
Use edge devices to bring more of your IIoT processes in-house. While this won’t prevent cloud-related issues, it will ensure more of your information is localized.
Regularly update your network security and all IIoT device firmware, as these updates can patch major vulnerabilities.
Run regularly scheduled security audits to look for any gaps in your security.
Choose infrastructure which aligns with industry standards like ISO 27001. Some platforms like Matterport will also offer enterprise-grade security features including secure cloud hosting and role-based access control.
Security is a full-time job, especially where the IIoT is concerned. If your IT resources are limited, consider expanding your team or partnering with security specialists to maintain strong defenses.
Retrofitting “dumb” devices
It’s not uncommon for manufacturing locations to have older equipment, or “dumb” devices, that predate IIoT tech. Fortunately, you can still make these devices IIoT compatible.
Depending on the device, you may need to start by swapping the legacy sensors out with smart sensors that are IIoT compatible. Then, you need to make sure your network is set up properly for IIoT, and that legacy devices are capable of interfacing with the network. You may need a gateway device to make the latter happen.
You also need to set up the right software to ensure you can access all the IIoT data you'll be receiving. Ideally, you should find a single platform that can handle all your various sources of data, or at the very least, a platform that allows for plug-ins.
Lastly, you need the right IIoT security in place, per the previous point.
Training and education
Going from pre-IIoT devices to IIoT-compatible devices and software is a big leap. This typically entails training and the time and cost that goes with it.
If you don’t have anyone internal that can help with training, bring in a consultancy or agency that specializes in IIoT devices. Assign internal stakeholders that are comfortable owning their part of manufacturing. These people can act as training leads and help their team stay current with any updates.
It’s important you hold regular training sessions, as software and device interfaces will update and change over time. The benefits of IIoT devices can only be realized if your team is trained up and capable of using them to the fullest!
Ready to see how digital twins can power your IIoT transformation? Start your free trial or contact our team to learn how Matterport can support your remote operations and facility management needs.
