IoT Edge 101

What is Edge Computing?

Edge computing pushes the intelligence, processing power and communication capabilities directly into devices.  It enables analytics and data gathering to occur at the source of the data.

What is the difference between Edge Computing and Fog Computing?

Both fog computing and edge computing involve pushing intelligence and processing capabilities down closer to where the data originates.

The critical difference between the two architectures is exactly where that intelligence and computing power is placed:

  • Fog computing pushes intelligence down to the local network level of network architecture, processing data in a fog node or IoT gateway.
  • Edge computing pushes the intelligence, processing power and communication capabilities of an edge gateway into devices. 

What are the benefits of Edge Computing?

The general benefits commonly associated with Edge Computing are:

  • Reduced Latency – no need for round trip communication to the cloud
  • Improved Bandwidth Efficiency – as not all data is required to be sent over the network to the cloud
  • Cost Savings – believed that it is more cost efficient to act on the data locally than processing in the cloud
  • Increased Security and Privacy – localized data is viewed as more secure
  • Protocol translation & data normalization

What are the Key Drivers Behind Edge Computing?

Edge computing is primarily driven by the need to address:

  • Real-time Insights
  • Localized Action
  • Location Challenges
  • Network Constraints
  • Volume & Velocity of Data Generated
  • Security of assets and data

What are common Edge Computing Verticals?

Edge computing is applicable across many different market verticals:

  • Agriculture
    • Farming, forestry, livestock, fisheries, agricultural equipment
  • Datacenters
    • IoT-specific growth, as well as IoT applications within the data center
  • Energy and Utilities
    • Electricity, oil, gas, water infrastructure
  • Health
    • Hospitals and medical equipment, telehealth, wearables
  • Industrial – Manufacturing & Mining
    • Manufacturing, construction, mining
  • Military
    • Battlefield equipment and soldiers, vehicles and aircraft
  • Retail
    • Interactive displays, inventory management, point of sale
  • Smart Buildings
    • Access control and surveillance, employee tracking, HVAC, elevators
  • Smart Cities
    • Lighting, waste management, traffic, and congestion optimization
  • Smart Homes
    • Thermostats, appliances, cameras, speakers
  • Transportation
    • Fleet telematics, civilian and commercial aircraft, ships
  • Wearables
    • Fitness trackers, smart watches, augmented and virtual reality equipment

What are the critical challenges around Edge Computing?

  • Confusion – fragmentation fuels confusion around what vendors have and where they fit in the ecosystem
  • Lack of Expertise – OT users, are not accustomed to IT
  • Domain Requirements – analytics solutions often require a deep understanding of the use case to ensure optimum value
  • Heterogeneity – addressing the vast variety of asset types, data, and networking technologies is a challenge

What are the components of a typical Edge Computing solution?

  • Hardware/Gateways/Servers
  • Protocol Conversion
  • Device Management
  • Analytics
  • Protocol Ingestion
  • Data Formatting
  • Connectivity Management
  • Security Management
  • 3rd party ecosystem


More in the next post .. stay tuned.

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