2-2-Overview of IoT Infrastructure: Prerequisites and Challenges - Dr. Marc Ibrahim
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"ICT in Lebanon: Towards a Brighter Future" A conference at the Order of Engineers & Architects - Beirut - Lebanon December 4,5 & 6 - 2018
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2-2-Overview of IoT Infrastructure: Prerequisites and Challenges - Dr. Marc Ibrahim
- 1. Overview of IoT infrastructure: Prerequisites and Challenges Marc Ibrahim marc.Ibrahim@usj.edu.lb December 4-6, 2018
- 2. Internet of Things marc.ibrahim@usj.edu.lb 2 IoT definitionS
- 4. marc.ibrahim@usj.edu.lb 4 Things Gateway Cloud ActuatorsSensors MCU/CPU Operating system Com. protocols Hardware Power Management Interfaces/ Connectors Operating system Fog Computing Security Operating system Edge computing Hardware Protocols MQTT, CoAP, HTTP, etc. IoT Com. BLE, Zigbee, LoRa, etc. Mgt. Cloud connectivity Mgt. Data Mgt. Custom. App. Storage Security Com. Protocols Analytics Mgt. Control Decision IoT Infrastructure Physical Realm Network Virtual Realm IoT Stack Internet stack IoT Stack
- 5. Size AutonomyCost Things requirements marc.ibrahim@usj.edu.lb 5 Application Battery (years) Consumer – wearables 1-3 Assisted Living / Medical 2-5 Smoke detector – home/enterprise 5 Industrial – asset tracking 2-10 Water/gas metering 15
- 6. Things requirements / criteria marc.ibrahim@usj.edu.lb 6 Things Processing capabilities (Controller) Miniaturization (computer economics) Integrated precision-analog capabilities (diversified sensing and actuating capabilities) Cost (design-prototype-produce own devices, use existing) Power consumption (low-power controller, deep sleep) Communications capabilities Tx/Rx Controller Sensors/ Actuators
- 7. Cloud – IoT platforms Send data to terminal Collect & Make sense of data marc.ibrahim@usj.edu.lb 7 Internet server IoT cloud Bytes Devices/Network management capabilities
- 8. Analytics requirements IoT Analytics Tactical Analysis Dashboards Alerts & Notifications Operational reporting Strategic Analysis Predictive analytics Geospatial analytics Time series analytics Pattern recognition marc.ibrahim@usj.edu.lb 8
- 9. Analytics challenges marc.ibrahim@usj.edu.lb 9 Integrating Data From Multiple Sources Collecting Data But Not Doing Analytics Messy & Unstructured Data Analysis Takes Too Long Too Much Data Data Security & Privacy Source: James Brehm & Associates. IoT Data Analytics Survey Results. The Connected Conversation Volume 2 / Issue 8 / October 2016
- 10. IoT platform selection Providers: • Microsoft Azure IoT, Amazon AWS IoT, Google cloud, Thingworx, Siemens Mindsphere, Watson IoT, GE Predix, Carriots marc.ibrahim@usj.edu.lb 10 Scalability Flexibility Interop. (Standard. Protocols, APIs) App enablement, dev. E2E Security Privacy Edge Capabilities Management (Devices & network) Pricing model Analytics & intelligence Integration IoT platform Checklist 260 360 450 2015 2016 2017
- 11. Network requirements Data Rate Delivery Delay marc.ibrahim@usj.edu.lb 11 3D’s of classical networks Consumption Coverage Cost 3C’s of IoT networks Down UP Down UP New technologies are needed
- 12. IoT communication standards marc.ibrahim@usj.edu.lb 12 NFC RFID < 10 cm < 5 km < 100 km Proximity Bluetooth Z-Wave Zigbee Wifi Short range Long range Cellular (licensed) 2/3/4 G LPWA (licensed) NB-IoT, LTE-M LPWA (unlicensed) LoRa, Sigfox, Ingenu, Dash7, Weightless RFID
- 13. Short-range communications Requirements low-rate low-power Relaying capabilities marc.ibrahim@usj.edu.lb 13 PHY Connect sensors together Network Data Link Connect sensors to the Internet Short-range communications Addressing Routing Links Access Low-rate Low-power NewStandards required
- 14. Short-range communications marc.ibrahim@usj.edu.lb 14 802.15.4 802.15.4 (CSMA/CA) Network (sec. routing,…) Application 6LoWPAN Adapt. IPv6 UDP CoAP-MQTT Zigbee 6LoWPAN WBAN BLE Radio BLE Link LR-WPAN 802.15.6 Host layers App. Bluetooth Low Energy 802.11h (900 MHz) 802.11h (CSMA/CA) Wi-Fi HaLow Main SRD standards • Mainly unlicensed spectrum. 2.4 GHz most used. • Implantable BSN: 401-406 MHz 802.15.6 (CSMA/CA, Aloha)
- 15. BLE example Home network example Energy: • BLE Chip with 180 mAH coin cell battery => 18 hours, 21.6 million transactions. • If 1 transaction/ 30 seconds => 20.5 years !! marc.ibrahim@usj.edu.lb 15
- 16. LPWAN (Low-Power Wide Area Network) marc.ibrahim@usj.edu.lb 16 Long-range radio technology with low Tx power High sensitivity <-140dBm (Bluetooth: -90 dBm, ZigBee: -120 dBm) High things density Very loose throughput and latency requirements
- 17. Comparisons marc.ibrahim@usj.edu.lb 17 Data rate Device/radio chipset cost Radio subscription cost CoverageDensity (term./km2) Battery life Latency Short Range Cellular LPWA
- 18. Use cases marc.ibrahim@usj.edu.lb 18 On-battery things – no access to power Large deployment area Tiny data volume per thing Uses cases: agriculture, forestry, building, e-health, industrial, retail, smart cities, supply chain
- 19. LPWA technical criteria marc.ibrahim@usj.edu.lb 19 NB- IoT Freq. bands (MHz) 169, 433, 915, 868 868(EU), 902(NA) 2400 2G & LTE Bandwidth (kHz) EU: 8x125 0.1/0.6 40x1 MHz 200KHz Unlicensed band Duty cycle (%) 0.1 or 1 0.1 or 1 Latency seconds 140 mess/day (UL) seconds seconds Bi-directional Limited downlink TX up (dBm) EU: 14 EU: 14 20 20-23 Data rate (kbps) up/down: 0.3-50 up < 0.3 up: 600, down:150 up/down: 250 Nodes/BS up 50k 50k 500k 100k Max payload 243 bytes 12 bytes 10 kbytes 1600 bytes Range (km) 2-15 10-50 15 35
- 20. LPWA other criteria marc.ibrahim@usj.edu.lb 20 NB- IoT Ownership - deployment Closed Hardware (Semtech) Open network / Private deployment Open Hardware Closed network Sigfox deployment Mixed private/ingenu deployment Mobile Operator deployment QoS Best Effort Best Effort Best Effort Managed Model LoRaWAN alliance Proprietary Proprietary 3GPP Roaming Requires networks collaboration Straightforward LTE
- 21. Battery life requirement – LoRa case marc.ibrahim@usj.edu.lb 21 Tx (50 mA) Rx (28 mA) LoRa adapter off (5 mA) Deep sleep (0.06 mA) Power modeling (ESIB-USJ)
- 22. Radio coverage – LoRa case Radio measurement campaign (ESIB-USJ) marc.ibrahim@usj.edu.lb 22 110 m 50m Urban Rural Indoor 𝑷𝑳 = 𝟏𝟎𝒏 𝐥𝐨𝐠 𝟏𝟎 𝒅 𝒌𝒎 + 𝑷𝑳 𝟎 + 𝑳 𝒉 𝑬𝑫 ∗ 𝐥𝐨𝐠 𝟏𝟎 𝒉 𝑬𝑫 𝑃𝐿 = 41.79 log10 𝑑 𝑘𝑚 + 102.86 − 6.3 ∗ log10 ℎ 𝐸𝐷 Sℎ𝑎𝑑𝑜𝑤𝑖𝑛𝑔 ~ 𝑁 0, 𝜎 = 7.2 𝑑𝐵 Enhanced radio model
- 23. The future of LPWA: growth and coexistence marc.ibrahim@usj.edu.lb 23
- 24. Expected LPWA deployments in Lebanon OGERO • LoRa • Cellular Other deployments • Lora • Ingenu Suggestions • Open LoRa to private use marc.ibrahim@usj.edu.lb 24
- 25. THANK YOU
Editor's Notes
- A lot of
- IoT ecosystem. The infrastructure is three fold: The physical realm, the things, The network And the data repository on the cloud The things a Cloud: describe management of devices and network gateways
- There are a variety of analytics associated with data collected from IoT. Most companies are generating what we would call “tactical analytics”. Tactical analytics typically provide a status or a summary based on single point in time or some sort of exception to an established threshold. Deliverables associated with tactical analytics include alerts and notifications or operational reports and dashboards. Fewer companies are generating what we call “strategic analytics”. A key characteristic of strategic analytics is that they typically include the evaluation of data over a period of time rather than a point in time. Strategic analytics may also incorporate other data sources, including data not collected from sensors or devices that enrich the source data. Deliverables associated with strategic analytics allow for predictive and pattern recognition analysis. Tactical and strategic analytics can be equally important within an IoT solution. An example of tactical analytics would be a notification that an engine’s fuel pressure has exceeded an established threshold, which enables a dispatching system to quickly deploy a service technician to diagnose and repair the engine before it fails. Strategic analytics would be an evaluation of an engine’s performance over time across multiple performance measures that lead to a more efficient maintenance schedule for all engines or possibly inform the design of a new engine. Both types of analytics are critical to a business and contribute to the value derived from IoT. Generally speaking, there’s more data infrastructure, computing, and storage required for strategic analytics, and that’s likely a key driver of why tactical analytics is currently far more common than strategic analytics. But the true value of IoT is when an analytic solution can provide the benefits of both tactical and strategic analytics.
- Environment and electrical safety (including the Restriction of Hazardous Substances Directive and Energy Star compliance, as well as tests for issues like overheating and electric shock). Communication protocols (before you label your gadget as Bluetooth-compatible, you have to test it in certified labs). Electromagnetic & radio-frequency interference (you need to prove the performance of your device won’t be affected by other connected devices within Wi-Fi/BLE/cellular network range, while the device itself conforms to the electromagnetic radiation exposure standards). Product-specific (such as skin tests required for devices which come in contact with the skin).