The Internet of Things (IoT) and IoT edge computing have been creating a buzz in the tech world for a number years. And today, IoT and edge computing are on course to see spectacular growth in the next decade, fueled by a range of factors from the desire to gain insights from devices in far-flung places to a need for operational efficiency and ROI.
Want to learn how to leverage IoT in business? You’ve come to the right place. This article explores the transformative power of IoT by delving into ten specific ways it could reshape your business’s digital operations.
Whether you’re strategizing a long-term plan to integrate IoT and edge computing into your business operations, or simply looking to learn something new, we’ve included a range of interesting industries and use cases likely to experience rapid development. Let’s dive in!
Key Takeaways
- IoT edge computing processes data closer to connected devices—like sensors, machines, and gateways—so businesses can act in real time
- It helps reduce latency, improve reliability, strengthen security, and lower bandwidth costs by filtering data before it reaches the cloud
- Organizations use edge computing to transform operations across utilities, manufacturing, healthcare, retail, transportation, and agriculture through faster insights and automation
- The best edge strategies combine local intelligence with centralized visibility, using hybrid cloud tools to manage and secure distributed devices at scale
How the Internet of Things Connects Our World
IoT is a network of connected devices embedded with sensors, software and connectivity capabilities that enable them to collect and exchange data. The capabilities of the IoT that drive business efficiencies are at the root of the enormous growth of the Internet of things. In fact, Statista forecasts that revenue in the IoT market will reach $621.6B by 2030 — a figure that will have tripled from 2020.
IoT devices range from everyday objects, such as a Vonage business phone or a home automation device, to connected vehicles, robotics, industrial monitoring and automation equipment and critical infrastructure that supplies energy and water to our cities. The underlying theme is that these devices can communicate with one another over wireless networks to provide an array of benefits such as true automation in Industry 4.0 applications, remote infrastructure management, and edge intelligence.
Edge computing is reshaping business’ operations across several sectors. While it requires careful consideration and implementation, there are numerous ways your business can leverage intelligence at the edge in the digital age.
What Are the Key Benefits of IoT Edge Computing and IoT for Businesses?
Before we look at the specific benefits, it helps to define what edge computing is—and how IoT edge computing applies it to connected devices.
- Edge computing: A distributed computing model where data is processed near its source (devices, gateways, routers) instead of in a centralized cloud.
- IoT edge computing: Applying edge computing to IoT environments to enable real-time analytics, automation, and security controls at or near devices.
With that foundation, let’s explore the business advantages edge computing brings to IoT deployments — especially in environments that require speed, reliability, and security.
Here are the overarching benefits of IoT edge computing that you should know about:
- Reduced latency: By processing data closer to edge devices, you’ll minimize the latency associated with sending data to a remote server for processing. This is crucial for real-time applications that require near-instantaneous responses to function correctly, which includes many IT devices.
- Bandwidth optimization: Edge computing reduces the need for transmitting large volumes of raw data to the cloud, as it only sends relevant or aggregated data. This helps optimize bandwidth usage and reduces network congestion, which in turn, can reduce your operational costs.
- Enhanced reliability of tech: With edge computing, critical applications can continue operating even without an Internet connection. Local processing and decision-making capabilities allow the system to remain functional, ensuring business continuity.
- Improved data privacy and security: Edge computing IoT devices reduce the exposure of sensitive data by processing it locally instead of sending it to the cloud. Such a model is attractive to industries where data protection is critical, such as healthcare, finance, utilities and infrastructure, where cyberattacks can have disastrous consequences.
- Access to real-time insights: By analyzing data at the edge, your business can extract immediate insights and take timely actions. This enables faster response times, proactive maintenance and more efficient operations.
In short, edge computing in IoT devices enables businesses to take computational power into their own hands and enhance operations for greater efficiency in the digital age. And today, network-wide management tools can provide a "single pane of glass" for gaining insights and instant notifications from across the network. For instance, with Digi Remote Manager®, you can track and manage all of your IoT devices in a single, intelligent network management interface.
When Should You Use Edge vs. Cloud Computing?
Edge computing and cloud computing are complementary—not competing—approaches. The right model depends on how quickly decisions need to be made, where data is generated, and how reliably systems must operate.
Use edge computing when:
- You need real-time or near-real-time response, such as for automation, safety systems, or predictive maintenance
- Devices operate in remote or bandwidth-constrained environments with intermittent connectivity
- Large volumes of data (video, sensor streams, telemetry) should be filtered or analyzed locally before transmission
- Privacy, security, or regulatory requirements require sensitive data to remain close to its source
Use cloud computing when:
- You need centralized analytics, long-term data storage, or cross-site visibility
- Workloads are not latency-sensitive and can tolerate network delays
- You’re aggregating data from many locations to support business intelligence, reporting, or AI model training
Use a hybrid edge-to-cloud model when:
- Local systems must act immediately, but insights still need to be shared centrally
- You want edge intelligence combined with cloud-based monitoring, orchestration, and updates
- Scalability, visibility, and control across distributed assets are as important as local autonomy
In practice, most IoT deployments rely on a hybrid architecture—processing critical data at the edge while using the cloud as a centralized control and analytics layer.
10 Ways IoT and Edge Computing Can Transform Business Operations
To illustrate the advantages of IoT in business mentioned above, let’s explore ten important use cases showing how edge computing IoT technology is emerging as a powerful driver in digital transformation.
1. Smart Grids
IoT enables intelligent grid systems by connecting various energy assets, such as power plants, substations and meters, through a network of sensors and communication devices. These IoT devices collect real-time data on energy generation, consumption patterns and grid conditions.
IoT devices in practice: Smart meters with built-in communication modules
For instance, smart meters equipped with IoT technology can measure energy usage at specific intervals and transmit the data wirelessly. This data allows utility companies to optimize energy distribution, balance loads and detect faults, resulting in more efficient energy management and reduced costs.
- Business outcome: Reduce outage time, improve grid reliability, and increase operational efficiency
- Edge advantage: Local processing enables faster fault detection and automated response without cloud latency
- Typical devices: Smart meters, grid sensors, edge gateways/routers, SCADA-connected controllers
2. Environmental Monitoring
IoT devices with in-built sensors and data loggers are crucial in environmental monitoring. These devices can collect data on anything from air quality, water quality and soil conditions to biodiversity indicators.
The device can collect and analyze this data, only alerting external systems when it passes threshold levels. For instance, IoT-enabled air quality sensors can measure pollutant levels in real time, enabling authorities to identify pollution hotspots and take immediate corrective action.
IoT devices in practice: Environmental sensors installed in a vineyard
The device can collect and analyze this data, only alerting external systems when it passes threshold levels. For instance, IoT-enabled air quality sensors can measure pollutant levels in real time, enabling authorities to identify pollution hotspots and take immediate corrective action.
- Business outcome: Improve safety, comply with environmental regulations, and respond faster to hazardous events
- Edge advantage: Edge analytics filters and flags abnormal conditions instantly, even in remote areas with limited connectivity
- Typical devices: Air/water quality sensors, weather stations, edge gateways, cellular routers
- IoT devices in practice: Environmental sensors feed data to local compute that triggers alerts for threshold breaches and only transmits relevant data upstream.
3. Connected Buildings and Building Security
One of the latest trends in the construction industry is a shift toward connected buildings.
In these smart buildings, occupancy sensors can detect the presence of occupants, allowing for optimized energy usage by automatically adjusting lighting and HVAC systems. Smart thermostats use IoT technology to learn user preferences and adjust temperature settings accordingly.
Finally, IoT-enabled surveillance cameras provide real-time video feeds and alerts for enhanced security and remote monitoring.
IoT devices in practice: Security monitoring in a manufacturing facility via distributed security cameras
- Business outcome: Reduce energy consumption, improve safety, and enhance public services through real-time operational visibility
- Edge advantage: Edge controls building and city systems locally for faster response, improved uptime, and reduced bandwidth usage
- Typical devices: HVAC sensors, lighting systems, traffic sensors, surveillance cameras, edge gateways/routers
- IoT devices in practice: Building systems stream data to edge devices that optimize energy usage and manage critical operations locally while syncing aggregated data to city platforms
4. Supply Chain Management
IoT devices can be deployed throughout the entire supply chain to provide real-time visibility and tracking.
Radio frequency identification (RFID) tags attached to products or packaging enable accurate identification and tracking at various stages of the supply chain. GPS trackers monitor the location and movement of goods, allowing businesses to optimize logistics and provide customers with real-time shipment updates.
Meanwhile, temperature sensors ensure the integrity of perishable goods by monitoring temperature conditions during storage and transportation.
IoT devices in practice: RFID tags attached to individual products or pallets
- Business outcome: Reduce delays, prevent losses, and improve inventory accuracy and delivery performance
- Edge advantage: Edge computing supports real-time tracking and condition monitoring (temperature, location, vibration) without relying on constant cloud connectivity
- Typical devices: GPS trackers, cold chain sensors, smart containers, vehicle gateways, cellular routers
- IoT devices in practice: Fleet and shipment sensors stream data to an edge gateway that validates conditions, triggers alerts for exceptions, and syncs summaries when connectivity is available
5. Self-Driving Cars
Technology is changing the way we interact with others and conduct daily activities. One exciting use case is self-driving cars.
IoT plays a crucial role in enabling connected vehicles and driverless cars by connecting various vehicle components and systems. Devices such as cameras and LiDAR scanners collect data on the vehicle's surroundings, including road conditions, obstacles and traffic patterns.
IoT devices in practice: Autonomous vehicle utilizing LiDAR scanners, sensors and connected vehicle technology
This data is processed in real time by onboard computers to make informed decisions on navigation, speed and driving behavior. Self-driving cars can optimize routes, improve fuel efficiency and enhance road safety through advanced IoT-enabled technologies.
- Business outcome: Enhance safety, reduce accidents, and enable faster decision-making for connected and autonomous mobility systems
- Edge advantage: Edge computing supports ultra-low-latency decision loops (object detection, navigation, hazard response) without reliance on cloud processing
- Typical devices: Vehicle sensors (lidar, radar), onboard compute units, roadside edge gateways, 5G/cellular routers
- IoT devices in practice: Vehicles and roadside systems process sensor data locally for immediate actions while sending only summarized telemetry for long-term analysis and fleet optimization.
6. Customer Service
IoT technologies are transforming call center operations by providing advanced features and capabilities. For example, VoIP phone features integrated with IoT enable call centers to streamline communication processes, such as call routing, call recording and intelligent call analytics.
IoT devices in practice: VoIP phone systems with advanced call center technologies
These features enhance the efficiency and effectiveness of customer interactions, enabling agents to provide a personalized service and improve customer satisfaction. In addition, IoT-powered call center technologies leverage real-time data and analytics to provide agents with valuable insights about customers, enabling them to deliver more targeted and proactive support.
- Business outcome: Improve customer satisfaction, reduce churn, and resolve issues faster through proactive support
- Edge advantage: Edge computing enables real-time monitoring and local analytics so service issues can be detected and addressed before they impact customers
- Typical devices: Connected products, sensors, edge gateways, remote monitoring systems, service dashboards
- IoT devices in practice: Devices continuously send operational and performance data to an edge platform that flags abnormal behavior and triggers alerts or automated support actions
7. Healthcare
IoT has revolutionized healthcare by enabling remote patient monitoring and connected medical devices.
Wearable devices, such as biosensors and medical implants, collect real-time health data from patients and transmit it securely to healthcare providers. This allows for practitioners to continuously monitor vital signs, administer medication and manage diseases.
IoT also facilitates telehealth services, enabling virtual consultations and remote diagnosis. Connected medical devices, like smart insulin pumps or cardiac monitors, ensure accurate and timely healthcare interventions.
That means you could be seen by a doctor from the other side of the world.
IoT devices in practice: Medical wearables that monitor steps, heart rate and other metrics.
- Business outcome: Improve patient outcomes, reduce readmissions, and enable safer remote care
- Edge advantage: Edge processing supports near-real-time monitoring, privacy-preserving analytics, and uninterrupted operation even if cloud access is limited
- Typical devices: Wearables, medical monitors, edge gateways, secure routers, hospital IoT systems
- IoT devices in practice: Patient data is processed locally for rapid alerts (e.g., abnormal vitals), while only essential data is securely transmitted for clinician review
8. Predictive Maintenance
IoT-enabled predictive maintenance strategies leverage data from devices to monitor technical equipment health in real time. These sensors collect data on various parameters, such as temperature, vibration and energy consumption.
By analyzing this data using machine learning algorithms, businesses can identify patterns and anomalies that indicate potential equipment failures. This proactive approach allows for timely maintenance interventions, reducing downtime and extending equipment lifespan.
IoT devices in practice: Condition monitoring in industrial machinery
- Business outcome: Reduce downtime, extend equipment life, and lower maintenance costs
- Edge advantage: Edge processing detects failures early by analyzing vibration, temperature, and performance data locally in real time
- Typical devices: Condition monitoring sensors, industrial gateways, edge computers, machine controllers
- IoT devices in practice: Equipment sensors stream telemetry to an edge device that performs local pattern detection and sends only exceptions or summary insights to the cloud.
9. Agricultural Operations
IoT is transforming farming as we know it through precision agriculture techniques.
For instance, autonomous recording stations provide real-time data on soil conditions, weather conditions and patterns and crop health. Farmers can access this data remotely and make informed decisions on irrigation schedules, fertilization and pest control.
The availability of modern cellular routers makes reliable connectivity possible even in environments where traditional wired cabling doesn’t make sense, such as in agricultural settings.
In this way, IoT-enabled agricultural operations optimize resource usage, reduce environmental impact and return greater crop yields.
IoT devices in practice: Soil moisture and equipment monitoring devices in agriculture
- Business outcome: Increase crop yield, reduce water and fertilizer waste, and improve sustainability
- Edge advantage: Edge systems enable local decision-making and automation across large, rural environments with inconsistent internet access
- Typical devices: Soil and moisture sensors, drones, irrigation controllers, rugged edge routers/gateways
- IoT devices in practice: Field sensors and irrigation equipment connect to an edge gateway that optimizes watering schedules and sends periodic reports to centralized systems
10. Retail Operations
IoT applications in the retail industry can enhance customer experience and optimize inventory management. IoT devices, such as smart shelves and beacons, provide real-time inventory tracking, enabling retailers to efficiently manage stock levels and reduce out-of-stock situations.
Companies can leverage Dynamic QR Codes for business to create interactive and engaging experiences for customers, allowing them to access product information, promotions, and special offers by scanning QR codes with their smartphones.
Moreover, IoT enables seamless checkout experiences with technologies like RFID-enabled self-checkout or mobile payment solutions. You may want to take note of this feature in your next website markup to promote accessibility.
In fact, you’ll find IoT devices using edge computing techniques in a wide range of applications at the core of retail operations. From self-serve kiosks to the top-tier connectivity needed to implement connectivity for secure financial transactions, IoT technology is at the heart of modern commerce.
IoT devices in practice: RFID-enabled smart shelves that track inventory levels in real time
- Business outcome: Prevent stockouts, reduce shrink, and improve customer experiences with smarter store operations
- Edge advantage: Local analytics enables fast insights from cameras, RFID systems, and point-of-sale data without cloud delays
- Typical devices: RFID readers, smart shelves, cameras, POS systems, edge servers/gateways
- IoT devices in practice: In-store devices send data to a local edge platform that tracks inventory levels, identifies anomalies, and automates restocking alerts
Edge Computing Implementation Checklist
Successfully deploying IoT edge computing requires more than adding compute at the network edge. Use the checklist below to plan, pilot, and scale an edge strategy that delivers real business value.
- Identify latency-sensitive use cases: Focus first on workflows that require real-time response, local automation, or continuous operation during connectivity disruptions
- Define which data must be processed locally: Determine what data should stay at the edge for performance, privacy, or regulatory reasons—and what can be sent to the cloud for aggregation and long-term analysis
- Select the right edge hardware: Choose gateways, routers, or edge computers that support your compute needs, environmental conditions, and connectivity requirements
- Plan connectivity and failover: Design for reliable communication using cellular, Ethernet, or Wi-Fi, with redundancy to support remote or mission-critical environments
- Secure devices from day one: Implement device authentication, encryption, access controls, and secure boot to protect edge systems throughout their lifecycle
- Design for offline and degraded operation: Ensure edge applications can continue functioning—and store data locally—when cloud connectivity is unavailable
- Centralize monitoring and management: Use a unified platform to monitor device health, deploy updates, manage configurations, and maintain visibility across distributed edge assets
- Start with a pilot and scale intentionally: Validate performance, security, and operational processes in a limited deployment before expanding across sites or use cases
Frequently Asked Questions About IoT Edge Computing for Business
What business problems does edge computing solve?
Edge computing helps businesses address challenges such as high latency, unreliable connectivity, excessive cloud data costs, and slow response times. By processing data locally, organizations can enable real-time decision-making, improve uptime, enhance security, and operate effectively in remote or mission-critical environments.
How does edge computing reduce latency?
Edge computing reduces latency by eliminating the need to send data to distant cloud data centers for processing. Instead, analytics and decision logic run locally—often within milliseconds — making it ideal for applications like automation, safety systems, predictive maintenance, and real-time monitoring.
What industries benefit most from edge computing?
Industries with distributed assets and time-sensitive operations benefit most, including utilities, manufacturing, healthcare, transportation, retail, agriculture, and smart cities. These environments often require real-time insights, local autonomy, and reliable operation even when connectivity is limited.
Is edge computing more secure than cloud computing?
Edge computing can enhance security by keeping sensitive data closer to its source and reducing the amount of data transmitted over networks. Local processing, combined with encryption, device authentication, and access controls, can help organizations meet privacy and regulatory requirements. In practice, security is strongest when edge and cloud are used together in a well-designed hybrid architecture.
What are examples of edge computing devices?
Common edge computing devices include IoT gateways, industrial routers, embedded computers, and ruggedized edge servers. These devices collect data from sensors, machines, or cameras and perform local processing before forwarding selected data to cloud platforms for centralized analysis and management.
How do organizations manage edge devices at scale?
Managing edge devices at scale typically requires centralized tools for monitoring, configuration, security updates, and lifecycle management. While data processing happens locally, cloud-based management platforms provide visibility and control across thousands of distributed edge devices from a single interface.
What are the main challenges of edge computing
Key challenges include managing large numbers of distributed devices, ensuring consistent security and updates, integrating edge systems with cloud platforms, and designing architectures that balance local autonomy with centralized oversight. These challenges can be addressed with proper planning, standardized hardware, and robust device management strategies.
Conclusion
Edge computing is transforming business by enabling organizations to process IoT data closer to where it’s generated — reducing latency, improving reliability, and strengthening security. By combining local intelligence at the edge with centralized cloud management, businesses can act on real-time insights, operate effectively in remote or constrained environments, and scale IoT deployments more efficiently. Across industries such as utilities, manufacturing, healthcare, retail, transportation, and agriculture, edge computing helps turn distributed data into faster decisions and measurable operational improvements.
The Internet of Things is revolutionizing much of what we do online by facilitating a shift from cloud to edge computing.
What does this mean for businesses? In today’s digital landscape, it gives you more control of your digital footprint, unlocking new opportunities and bringing many benefits, such as affordability and security.
Regardless of your industry, you’re likely to see some form of disruption from IoT tech in the near future.
So, next time you ask a smart assistant to play your favorite music, check your daily steps with a wearable fitness tracker, or even track your pet with a smart collar, remember that you are experiencing just a taster of what this tech could one day become!
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About the Author
Ryan is an award-winning copywriter, with 20+ years of experience working alongside major US brands, emerging start-ups and leading tech enterprises. His copy and creative have helped companies in the B2B marketing, education and software sectors reach new customer bases and enjoy improved results. You can find him here on LinkedIn.
Editorial note: This blog post was first published in October of 2023 and republished in March of 2026.