Which Situation Would Benefit the Most by Using Edge Computing?

Few industries demand precision like healthcare. Lives can change in seconds, and that is why it is one of the situations that would benefit the most from using edge computing. The stakes are high, not just for patient outcomes but for data security and system reliability. According to IBM, the average cost of a healthcare data breach hit $11 million in 2023. However, the real cost comes when critical data is not where it needs to be.

Hospitals and care facilities now rely on a growing network of connected devices, including smart monitors, imaging systems, wearables, and IoMT platforms. These tools constantly generate data that clinicians need in the moment. But if all of that information has to travel to the cloud and back before decisions are made, the risk grows.

Edge computing examples in healthcare show just how vital local processing has become:

• Robotic surgeries assisted by 5G require real-time precision with no margin for delay
• Wearable trackers collect vital signs around the clock, often in remote or rural areas
• Pharmaceutical chains need edge systems to monitor temperature and handling, ensuring patient safety

Edge computing keeps this data close to the source, enabling faster insights and improving reliability even if internet access fails. It also supports HIPAA compliance by minimizing unnecessary data transfers.

At OTAVA, we provide secure, localized edge environments backed by our S.E.C.U.R.E.™ Framework. We help providers operate with confidence, knowing that patient data stays protected and accessible exactly when and where it matters most.

Modern manufacturing thrives on speed, accuracy, and control. Machines run 24/7, churning out data on everything from temperature and pressure to vibration and wear. Any delay in processing that data can lead to costly mistakes or equipment failure. That is why manufacturing is another situation that would benefit the most from using edge computing.

Instead of routing every sensor reading through centralized systems, edge devices positioned directly on the floor can analyze and act on data instantly. For example, if a machine starts vibrating outside its safe range, an edge device can detect the issue and shut it down before a breakdown occurs. In such a case, there is no lag or downtime.

• Machine learning models run at the edge to catch subtle signs of wear or fatigue
• Local filtering reduces noise from thousands of sensor inputs, sending only high-value data to the cloud
• Manufacturing Execution Systems (MES) remain online even if the network goes offline, keeping production moving

Edge computing reduces latency and further adds resilience. In an industry where minutes of downtime can cost thousands, local processing acts as a safety net.

Through our partnership with Scale Computing, we offer hyperconverged edge systems designed for industrial environments. These solutions run close to the source, eliminate failure-prone chokepoints, and adapt to real-world conditions on the floor. 

At OTAVA, we help manufacturers cut waste, gain real-time visibility, and make every process sharper, faster, and smarter.

Retail lives and dies by experience. Whether someone is grabbing essentials from a grocery aisle or browsing high-end cosmetics, the expectation is the same: fast, intuitive service. 

When systems lag, customers walk. When shelves are empty, sales slip. In retail, milliseconds matter, and this is exactly the kind of situation that would benefit the most from using edge computing.

One well-known example: Target’s inventory reset caused an 87% drop in quarterly profit. Not because of bad products but because systems failed to anticipate customer demand. 

That is where edge comes in. By processing data right at the store level, edge infrastructure gives retailers instant visibility into trends, stock levels, and behavior without waiting for the cloud.

Use Cases

• Smart shelves that track inventory in real time and trigger restock alerts automatically
• Interactive displays that suggest personalized products as shoppers walk by
• Checkout-free models (like Amazon Fresh) where cameras, sensors, and AI handle transactions instantly

Benefits

• Speed: Customers move through the store without queues or delays
• Accuracy: Inventory reflects what is actually on the shelf and not what the system “thinks” is there
• Security: Local processing reduces the volume of personal data sent to the cloud

At OTAVA, we help retailers design store-level edge systems that work hand-in-hand with cloud infrastructure. We support national and global rollouts that stay fast, reliable, and responsive—without sacrificing control or customer trust.

Wind farms, oil rigs, and solar plants operate in isolated environments, often with unreliable connectivity. That makes energy one more situation that would benefit the most by using edge computing.

Edge enables these environments to process vast sensor data without waiting for slow or unstable cloud communication. When a fault is detected, an edge system can act before central IT even gets the alert. Local processing also means fewer data transfers, saving bandwidth and reducing latency.

Use Cases

• Anomaly detection on offshore rigs
• Real-time analytics for smart grid operations
• Wildlife monitoring in protected areas using edge AI

Benefits

• Reduces costs by minimizing cloud dependency
• Keeps operations running in remote or disconnected regions
• Helps organizations meet environmental and sustainability goals

At OTAVA, we deploy edge architecture that functions independently and securely, even in the harshest conditions. Our infrastructure spans from edge to core, ensuring utility providers gain insight without sacrificing control.

Autonomous vehicles must make safety-critical decisions in real time. These decisions cannot wait for the cloud. Self-driving cars, drones, and delivery robots represent yet another situation that would benefit the most by using edge computing.

An edge device inside a vehicle receives constant input from Lidar, radar, and onboard cameras. If a cyclist suddenly swerves into the lane, the system needs to react instantly. Cloud delays, even of a few milliseconds, introduce serious risk.

Edge computing examples in this space include:

• Real-time obstacle detection and response
• Local AI-driven route optimization based on current road conditions
• Vehicle-to-vehicle communication for convoy coordination

NVIDIA’s Jetson Pegasus platform can process up to 320 TOPS, showing how much compute power autonomous systems demand at the edge. We help mobility companies design hybrid environments that use the cloud for training and the edge for execution. Our goal is simple: real-time performance that keeps people safe.

At OTAVA, we design edge computing environments tailored to the exact needs of complex industries. Whether it is powering autonomous navigation, securing sensitive medical data, or enabling predictive factory insights, we build edge infrastructure that meets the moment.

Our systems integrate with existing cloud infrastructure to create a seamless experience from edge to core. With hardened security, high availability, and proven scalability, we help organizations deploy edge computing where it matters most.

Talk to our team today to future-proof your infrastructure.

• What Is Edge Computing?
• Edge Computing Examples in Manufacturing: How Smart Technology Is Transforming Production
• Edge to Cloud Computing in Finance: Enhancing Security and Performance