The Internet of Things (IoT) market is exploding, with over 25 billion connected devices expected by 2025 according to IoT Analytics. As more organizations adopt IoT technology, the ability to monitor and manage these complex systems is becoming critical. This article examines how IoT monitoring can deliver major benefits as well as pose notable challenges for businesses as we head into 2023 and beyond.
What Exactly is IoT Monitoring and Why Does it Matter?
IoT monitoring refers to the processes, tools, and platforms used to track IoT devices across the organization and collect data on performance, network activity, application usage, and more. It gives complete visibility into an enterprise’s connected assets and systems.
Key capabilities of IoT monitoring include:
- Asset management – Discover all connected devices and inventory assets
- Data collection – Ingest, normalize and store time-series IoT data
- Analytics – Analyze real-time and historical data to find insights
- Visualization – Create dashboards and tools to view data
- Alarming and alerting – Get notified when metrics cross thresholds
- Remote control – Remotely manage devices and systems
- User management – Manage access and permissions across users
Effective IoT monitoring provides several critical benefits:
- Increased operational efficiency
- Reduced costs
- Enhanced data-driven decision making
- Proactive risk management
- Regulatory and standards compliance
- New revenue opportunities
According to MarketsandMarkets, the IoT monitoring market size is predicted to grow from $9 billion in 2020 to over $47 billion by 2026. IoT adoption is accelerating across industries, and monitoring serves as the foundation that enables organizations to maximize value from IoT investments while minimizing risk.
Major Benefits of Implementing IoT Monitoring
Adopting IoT monitoring can transform business operations and create competitive advantage. Here are some of the top benefits:
1. Optimize Processes and Increase Efficiency
IoT monitoring gives complete visibility into daily operations and processes. By tracking equipment effectiveness, supply chain movements, facility energy consumption, and hundreds of other metrics, organizations can identify inefficiencies and optimize productivity.
For example, Maersk leveraged IoT monitoring to improve operational efficiency for its shipping vessels, achieving a 10% decrease in fuel consumption by analyzing engine performance data in real-time.
2. Reduce Costs through Predictive Maintenance
By analyzing real-time equipment sensor data combined with historical patterns, companies can predict failures before they happen. This prevents the high costs of unplanned downtime and maintenance.
GE estimates that predictive maintenance can reduce maintenance costs by up to 25% across industries like manufacturing, oil and gas, and aviation.
3. Drive Better Decisions with Real-Time Data
Access to real-time insights on operations, equipment, customers, market conditions, and more through IoT monitoring allows responsive data-driven decision making.
For example, UPS monitors its delivery vehicles extensively to gather data on driver behavior which is used to enhance safety training protocols and minimize accidents.
4. Enhance Customer Experiences
The data collected through connected sensors and devices provides tremendous insights into customer preferences and behaviors. Companies can deliver hyper personalized offerings and tailored engagement strategies.
Disney leverages IoT monitoring of its theme park guests to shorten lines and improve overall park satisfaction through real-time data and analytics.
5. Ensure Safety and Security
Continuous monitoring of IoT infrastructure allows early detection of issues that impact safety like equipment failures. It also enables prompt identification of and response to any suspicious network activity.
Bosch uses IoT monitoring in its smart factories to analyze data and predict safety risks and events. This has led to a nearly 50 percent decrease in reported incidents.
6. Meet Industry Compliance Standards
Ongoing oversight and tracking of IoT systems ensures all software, data practices, equipment processes and output meet legal and regulatory requirements.
IoT monitoring is critical for pharmaceutical companies to comply with Good Manufacturing Practices and maintain quality standards established by regulatory bodies like the FDA.
In summary, an effective IoT monitoring strategy is invaluable for increasing ROI of IoT deployments, creating operation efficiencies, enabling innovation and gaining competitive advantage for businesses. According to Microsoft, organizations with advanced IoT monitoring in place experience 30-50% higher ROI on IoT investments.
Real World IoT Monitoring Use Cases Across Industries
| Industry | Use Cases | Metrics Tracked |
|---|---|---|
| Manufacturing | Overall equipment effectiveness (OEE) Predictive maintenance Asset tracking |
Production output, downtime, quality, defects, wear and tear, vibration, temperature |
| Transportation | Fleet tracking and management Fuel consumption Driver safety |
Location, mileage, acceleration, braking, idling, engine diagnostics |
| Healthcare | Patient monitoring Medical equipment maintenance Asset management |
Vitals like heart rate, blood pressure, oxygen levels, activity tracking, equipment calibration, cleaning, servicing |
| Energy | Smart grid optimization Renewables performance Outage monitoring |
Generation, consumption, load balancing, transmission efficiency, weather data, asset health |
| Smart Buildings | HVAC and lighting automation Leak monitoring Access controls |
Occupancy, air quality, usage patterns, temperature, leak sensors, security systems activity |
| Retail | Inventory optimization Customer engagement |
Inventory levels, sales data, foot traffic, wait times, buying behaviors, staffing needs |
| Supply Chain | Cargo tracking Fleet management |
Location, temperature, humidity, handling, cargo load, ETAs, checkpoints |
Key Challenges to Address with IoT Monitoring
While delivering immense value, IoT monitoring also comes with distinct challenges that must be addressed:
- Security vulnerabilities – Broader connectivity and more endpoints substantially increase potential attack surfaces for hackers. Strong network security and access controls are imperative.
- Data overload – The sheer volume of data generated can overwhelm analytics tools and staff. Prioritizing key metrics and filtering data is critical.
- Integration complexities – IoT monitoring tools must integrate with diverse legacy enterprise IT systems and databases which is often difficult.
- Prohibitive costs – The software, hardware, and tools required represent major upfront and ongoing investment. Demonstrating ROI is key.
- Expertise shortages – Data scientists, infrastructure engineers, cybersecurity analysts, and developers are required and can be challenging roles to fill.
- Lack of internal skills – Most organizations lack staff knowledgeable in IoT monitoring best practices. Training or external help is needed.
- Device diversity – Supporting and managing many different makes, models, and types devices with varying protocols is enormously complex.
- Compliance risks – Meeting constantly evolving regulatory standards like HIPAA requires ongoing vigilance and oversight.
While substantial, these challenges are not insurmountable. Let’s examine strategies and best practices organizations can leverage to overcome them.
Approaches to Effective IoT Monitoring
IoT monitoring tools utilize a variety of techniques and analytics capabilities to provide the right functionality across diverse environments. Common approaches include:
Rules-Based Monitoring – Establishing predefined rules and thresholds that trigger alerts when certain conditions are met. This is the most basic monitoring technique.
Anomaly Detection – Using machine learning algorithms to identify anomalies and detect patterns in massive volumes of IoT data that signal potential issues.
Predictive Analytics – Forecasting potential failures or problems before they occur based on statistical modeling of historical IoT data.
Stream Processing – Enabling real-time data monitoring through high throughput ingestion and analysis of endless streams of data from IoT systems.
Data Visualization – Creating graphical dashboards to visualize insights from complex IoT data in a simple, easy to absorb manner.
AIOps Platforms – Using artificial intelligence for IT operations to automate analysis of performance data across cloud, legacy IT, and IoT environments.
There are also three common architectural deployment strategies for IoT monitoring:
Cloud-based – All data is transmitted from IoT devices up to cloud platforms for monitoring and analytics. This provides unlimited scalability but can incur excessive data costs.
On-premise – The IoT platform and monitoring tools are deployed locally within the organization‘s data center infrastructure. This ensures full control and security of data but lacks scalability.
Hybrid – Blends cloud-based monitoring and analytics with on-premise gateways and data management. Provides the best of both cloud and local deployment strategies.
Choosing the Right IoT Monitoring Tools
With so many solutions on the market, selecting the right IoT monitoring platforms and tools for your organization can be daunting. Here is an evaluation of leading options:
Microsoft Azure IoT Hub – A fully managed cloud service that is highly scalable, secure, and integrates seamlessly with other Azure services like Azure Monitor. It supports millions of devices and enables bi-directional communication.
AWS IoT Core – Amazon’s cloud-based IoT monitoring platform with broad capabilities and robust security tools like role-based access control. It scales to billions of devices and trillions of messages.
GE Digital Predix – An industrial-strength IoT platform tailored to manufacturing that provides monitoring, analytics, and automation capabilities using Predix Machine.
PTC ThingWorx – An end-to-end IoT solution with advanced monitoring functionality including machine learning-driven anomaly detection and alerts.
IBM Watson – Leverages AI and sophisticated analytics to extract and monitor IoT data from connected devices and apply cognitive insights.
Splunk – A big data analytics platform great at aggregating and monitoring large volumes of machine data from across IT systems, including IoT environments.
There are also many other enterprise monitoring tools like PRTG, Nagios, Zabbix, and Datadog that provide robust monitoring capabilities. The ideal solution depends on your specific use case, industry, IT environment and technical expertise.
Best Practices for Implementing IoT Monitoring
Approaching IoT monitoring methodically and strategically will help maximize benefits while avoiding potential pitfalls. Recommended best practices include:
- Start small – Focus initial monitoring on the most critical assets and high-value use cases before scaling up.
- Prioritize security – Any monitoring program must have security at its foundation from day one.
- Leverage automation – Automated monitoring is far more efficient than manual methods which rapidly become unmanageable.
- Design key metrics – Determine the most meaningful KPIs to monitor to avoid unnecessary data overload.
- Inspect and adapt – Continuously evaluate monitoring effectiveness and promptly adjust rules and filters based on insights.
- Consider third-party support – Many organizations lack robust internal expertise to deploy monitoring and can benefit from external guidance.
- Plan for future integration – Architect the monitoring approach to support integration of new systems, tools, and data sources over time.
The Future of IoT Monitoring – Trends to Watch
As IoT adoption accelerates, IoT monitoring will rapidly increase in scope, sophistication, and intelligence. Key trends include:
- Rise of unified monitoring platforms spanning cloud, networks, IoT, user experience, and business KPIs
- Mainstreaming of predictive maintenance capabilities leveraging AI and advanced analytics
- Growth of digital twins for complex virtual modeling and simulation-based monitoring
- Shift from reactive to proactive and automated monitoring driven by maturing AIops
- Edge computing reducing data transmission costs allowing decentralized monitoring
- As-a-Service monitoring consumption models emerging as cloud offerings mature
- Blockchain enabling decentralized, trusted monitoring and automation across partners
- Greater focus on measuring monitoring ROI and driving business value
The future of IoT monitoring is bright. Organizations that start now building a robust IoT monitoring foundation will be poised to capitalize on this potential as the market evolves.
Conclusion
IoT monitoring is imperative to maximize value and minimize risk from IoT deployments as adoption accelerates. The benefits range from driving data-driven decision making to increasing operational efficiency, reducing costs, tightening security, and more. However, IoT monitoring also introduces significant technical, organizational and skills-based challenges that must be addressed through meticulous strategy and planning. Companies that leverage the best practices and top IoT monitoring platforms outlined in this guide will be primed for IoT success.