Sector use cases

We will now try to consider the typical use cases in a variety of industries adopting IoT and cloud analytics. When architecting the solution, we need to consider the scale, the bandwidth, real-time needs, and types of data to derive the correct cloud architecture, as well as the correct analytics architecture.

These are generalized examples - it is imperative to understand the entire flow and future scale/capacity when drawing a similar table:

Industry

Use cases

Cloud services

 Typical bandwidth

Real time

Analytics

Manufacturing

  • Operational technology 
  • Brownfield
  • Asset tracking
  • Factory automation
  • Dashboards
  • Bulk storage
  • Data lakes
  • SDN (hybrid cloud topology)
  • Low latency
  • 500 GB/day/factory part produced
  • 2 TB/minute mining operations

Less than 1s

  • Recurrent neural nets
  • Bayesian networks

Logistics and transport

  • Geolocation tracking
  • Asset tracking
  • Equipment sensing
  • Dashboards
  • Logging
  • Storage
  • Vehicles: 4 TB/day/vehicle (50 sensors)
  • Aircraft: 2.5 to 10 TB/day (6000 sensors)
  • Assets tracking: 1 MB/day/beacon
  • Less than 1s (real-time)
  • Daily (batch)

 Rule engines

Healthcare

  • Asset tracking
  • Patient tracking
  • Home health monitoring
  • Wireless health equipment
  • Reliability and HIPPA
  • Private cloud option
  • Storage and archival
  • Load balancing
  • 1 MB/day/sensor
  • Less than 1s: Life critical
  • Non-life critical: On each change
  • Recurrent Neural Networks (RNN)
  • Decision trees
  • Rules engines

Agriculture

  • Livestock health and location tracking
  • Soil chemistry analysis
  • Bulk storage - archiving
  • Cloud-to-cloud provisioning
  • 512 KB/day/livestock head
  • 1000 to 10000 head of cattle per feedlot
  • 1 second (real-time)
  • 10 minutes (batch)

Rules engines

Energy

  • Smart meters
  • Remote energy monitoring (solar, natural gas, oil)
  • Failure prediction
  • Dashboards
  • Data lakes
  • Bulk storage for Historical rate prediction
  • SDN
  • Low latency
  • 100-200 GB/day/wind turbine
  • 1 to 2 TB/day/oil rig
  • 100 MB/day/smart meter
  • Less than 1s: energy production
  • 1 minute: smart meters
  • RNN
  • Bayesian networks
  • Rules engines

Consumer

  • Real-time health logging
  • Presence detection
  • Lighting and heating/AC
  • Security
  • Connected home
  • Dashboards
  • PaaS
  • Load balancing
  • Bulk storage
  • Security camera: 500 GB/day/camera
  • Smart device: 1-1000 KB/day/sensor-device
  • Smart home: 100 MB/day/home
  • Video: less than 1s
  • Smart home: 1s
  • Convolutional neural nets (image sensing)
  • Rules engines

Retail

  • Cold chain sensing
  • POS machines
  • Security systems
  • Beaconing
  • SDN/SDP
  • Micro-segmentation
  • Dashboards
  • Security: 500 GB/day/camera
  • General: 1-1000 MB/day/device
  • POS and credit transaction: 100ms
  • Beaconing: 1s
  • Rules engines
  • Convolutional neural networks for security

Smart City

  • Smart parking
  • Smart trash pickup
  • Environmental sensors
  • Dashboards
  • Data lakes
  • Cloud-to-cloud services
  • Energy monitors: 2.5 GB/day/city (70K sensors)
  • Parking spots: 300 MB/day (80,000 sensors)
  • Waste monitors: 350 MB/day (200,000 sensors)
  • Noise monitors: 650 MB/day (30,000 sensors)
  • Electric meters: 1 minute
  • Temperature: 15 minutes
  • Noise: 1 minute
  • Waste: 10 minutes
  • Parking spots: every change
  • Rules engine
  • Decision trees
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