IoT and Communication Technologies for Smart Cities

IoT and Communication Technologies for Smart Cities
IoT and Communication Technologies for Smart Cities Samer Lahoud Smart Cities Nov. 6-7, 2018 Professeur associé Faculté d’ingénierie ESIB Université Saint-Joseph de Beyrouth
A Layered Vision of Smart Cities IoT and Smart Cities samer.lahoud@usj.edu.lb 2 Source: Schuilenburg, M. & Peeters, Smart cities and the architecture of security: pastoral power and the scripted design of public space, R. City Territ Archit (2018) 5: 13
A Layered Vision of Smart Cities IoT and Smart Cities samer.lahoud@usj.edu.lb 3 Source: Schuilenburg, M. & Peeters, Smart cities and the architecture of security: pastoral power and the scripted design of public space, R. City Territ Archit (2018) 5: 13 Smart People Education, Learning, and Knowledge
A Layered Vision of Smart Cities IoT and Smart Cities samer.lahoud@usj.edu.lb 4 Source: Schuilenburg, M. & Peeters, Smart cities and the architecture of security: pastoral power and the scripted design of public space, R. City Territ Archit (2018) 5: 13 Smart Governance Smart People Institutions, Partnerships, and Alliances Education, Learning, and Knowledge
A Layered Vision of Smart Cities IoT and Smart Cities samer.lahoud@usj.edu.lb 5 Source: Schuilenburg, M. & Peeters, Smart cities and the architecture of security: pastoral power and the scripted design of public space, R. City Territ Archit (2018) 5: 13 Smart Governance Smart People Smart Technology Institutions, Partnerships, and Alliances Education, Learning, and Knowledge Internet of Things
The Needs
Internet of Things § IoT device • Sensing • Computation • Transmission IoT and Smart Cities samer.lahoud@usj.edu.lb 7
Internet of Things § IoT device • Sensing • Computation • Transmission IoT and Smart Cities samer.lahoud@usj.edu.lb 8 Air quality
Internet of Things § IoT device • Sensing • Computation • Transmission IoT and Smart Cities samer.lahoud@usj.edu.lb 9 Air quality Solar energy
Internet of Things § IoT device • Sensing • Computation • Transmission IoT and Smart Cities samer.lahoud@usj.edu.lb 10 Air quality Solar energy Parking Spot
Internet of Things § IoT device • Sensing • Computation • Transmission IoT and Smart Cities samer.lahoud@usj.edu.lb 11 Air quality Solar energy Traffic control Parking Spot
The Case of IoT for Smart Cities § Smart waste management • Fill-level sensors on waste containers • Real time monitoring and predictive analytics • Optimizing waste collection routes and schedules IoT and Smart Cities samer.lahoud@usj.edu.lb 12
The Case of IoT for Smart Cities § Smart waste management • Fill-level sensors on waste containers • Real time monitoring and predictive analytics • Optimizing waste collection routes and schedules IoT and Smart Cities samer.lahoud@usj.edu.lb 13 40 km2 15 bins per km2 Total of 600 bins
The Case of IoT for Smart Cities § Smart waste management • Fill-level sensors on waste containers • Real time monitoring and predictive analytics • Optimizing waste collection routes and schedules IoT and Smart Cities samer.lahoud@usj.edu.lb 14 40 km2 15 bins per km2 Total of 600 bins
The Constraints on IoT for Smart Cities § Wide area coverage • Wireless communications • Scalable deployment • Cost efficient devices § Limited access to power sources • Long battery life operation § Very loose bandwidth and latency constraints • Adaptive radio and access mechanisms IoT and Smart Cities samer.lahoud@usj.edu.lb 15
The Constraints on IoT for Smart Cities § Wide area coverage • Wireless communications • Scalable deployment • Cost efficient devices § Limited access to power sources • Long battery life operation § Very loose bandwidth and latency constraints • Adaptive radio and access mechanisms IoT and Smart Cities samer.lahoud@usj.edu.lb 16 Do existing wireless technologies satisfy these constraints?
Faster is Not Always Better IoT and Smart Cities samer.lahoud@usj.edu.lb 17
Faster is Not Always Better IoT and Smart Cities samer.lahoud@usj.edu.lb 20 The sweet spot of Low Power Wide Area Networks
The Promises
IoT Market and Evolution § From $157B in 2016 to $457B by 2020 (GrowthEnabler) • Dominated by Smart Cities (26%), Industrial IoT (24%) and Connected Health (20%) IoT and Smart Cities samer.lahoud@usj.edu.lb 22 16 ERICSSON MOBILITY REPORT JUNE 2017 to increase at a CAGR of 21 percent, driven by new use cases. IoT device connections In the figure below, IoT is divided into short-range and wide-area segments. The short-range segment largely consists of devices connected by unlicensed radio technologies, with a typical range of up to 100 meters, such as Wi-Fi, Bluetooth and ZigBee. This category also includes devices connected over fixed-line local area networks and powerline technologies. The wide-area segment consists of devices using cellular connections, as well as unlicensed low-power technologies, such as Sigfox, LoRa and RPMA. Presently, the dominating technology in this segment is GSM/GPRS. 1.5 billion IoT devices with cellular connections by 2022 At the end of 2016, there were around 0.4 billion IoT devices with cellular connections. Due to increased industry focus emerged: massive and critical applications. Massive IoT connections are characterized by high connection volumes and small data traffic volumes, low-cost devices and low energy consumption. Many things will be connected through capillary networks.3 Critical IoT connections place very different demands on the network: ultra-reliability, availability, low latency and high data throughput. Declining modem costs, evolving LTE functionality and 5G capabilities are all expected to extend the range of applications for critical IoT deployments. There are, however, many use cases between these two extremes, which today rely on 2G, 3G or 4G connectivity. The first cellular IoT networks supporting massive IoT applications, based on Cat-M1 and Narrow Band-IoT (NB-IoT) technologies4 , were launched in early 2017. Several operators are expected to deploy cellular IoT networks in 2017. Connected devices (billions) 1 In our forecast, a connected device is a physical object that has a processor, enabling communication over a network interface Note: Traditional landline phones are included for legacy reasons 2 Including: Smart TVs, digital media boxes, Blu-Ray players, gaming consoles, audio/video (AV) receivers, etc. 3 Connected devices connecting to a wide-area network through a common gateway 4 Cat-M1 supports a wide range of IoT applications, including content-rich ones, and NB-IoT is streamlined for ultra-low throughput applications. Both these technologies are deployed in LTE networks 0 5 10 15 20 25 30 2020 2021 2022201920182017201620152014 Wide-area IoT Short-range IoT PC/laptop/tablet Mobile phones Fixed phones 16 billion 29 billion CAGR20222016 0.4 2.1 30% 5.2 15.5 20% 1.6 1.7 0% 7.3 8.6 3% 1.4 1.3 0% Source: Ericsson mobility report, 2017
The Battle for LPWAN IoT IoT and Smart Cities samer.lahoud@usj.edu.lb 23
The Battle for LPWAN IoT IoT and Smart Cities samer.lahoud@usj.edu.lb 24 Unlicensed LicensedSpectrum
The Battle for LPWAN IoT IoT and Smart Cities samer.lahoud@usj.edu.lb 25 Unlicensed LicensedSpectrum Global NationalDeployment Private
The Battle for LPWAN IoT IoT and Smart Cities samer.lahoud@usj.edu.lb 26 Unlicensed LicensedSpectrum Global NationalDeployment Private Average LowMaturity High
The Battle for LPWAN IoT IoT and Smart Cities samer.lahoud@usj.edu.lb 27 Unlicensed LicensedSpectrum Global NationalDeployment Private Average LowMaturity High Delay sensitiveQoS Delay tolerant
The Research on LPWAN IoT § Measure the performance • Conduct measurement campaigns (coverage, capacity, QoS, etc.) • Generalize measurements (empirical models, statistical distributions) § Compute performance bounds • Develop simulation platforms and theoretical models • Design benchmarks for comparison (e.g., LoRa vs NB-IoT) § Introduce new concepts or mechanisms • Test the validity and assess the impact (e.g., localization with LPWAN) IoT and Smart Cities samer.lahoud@usj.edu.lb 28
LoRaWAN for IoT § LoRaWAN is an IoT technology • Communication protocol and architecture using LoRa • Devices transmit without any coordination § LoRaWAN is supported by an alliance of industries § Future deployment in Lebanon • Tender for a national network (Sept. 2016) IoT and Smart Cities samer.lahoud@usj.edu.lb 29 Devices Gateways Network Server Cloud Services and Applications
What is LoRa? § LoRa is a robust modulation for wireless transmission • Variation of Chirp Spread Spectrum (CSS) • Uses Spreading Factors to increase the coverage § Operates in license-free bands • Lebanon: 868 MHz § Spectrum regulation • Transmit power limited to 14 dBm (25 mW) • 1% per sub-band duty-cycle limitation § Coverage can reach tens of kilometers • Record of 45 km in Bekaa § Data rates range from 300 bps to 5.5 kbps IoT and Smart Cities samer.lahoud@usj.edu.lb 30
Beirut Measurement Campaign IoT and Smart Cities samer.lahoud@usj.edu.lb 31 Gateway-ESIB Urban Beirut City 3m 1.5m 20cm LoRa Gateway at ESIB-USJ LoRa Transmitters
Coverage Test Points in the City of Beirut IoT and Smart Cities samer.lahoud@usj.edu.lb 32
A New Empirical Model for Propagation IoT and Smart Cities samer.lahoud@usj.edu.lb 33 PL = 41.8 ∗ log,- d/0 + 102.9 − 6.3 ∗ log,- h9: Shadowing ~ N 0, σ = 7.2 dB
Estimated LoRa Coverage in Beirut Smart City IoT and Smart Cities samer.lahoud@usj.edu.lb 34
Drive Test in the City of Beirut IoT and Smart Cities samer.lahoud@usj.edu.lb 40 LoRa at Rooftop of a car @ 1.6 m
LoRa is Very Low Power § Devices sending one message every 10 minutes • 1 year autonomy on a single battery charge! IoT and Smart Cities samer.lahoud@usj.edu.lb 41
Estimated Capacity of a LoRa Deployment § LoRa devices transmit without any coordination • Collisions can occur! • Mathematical model is necessary to estimate the capacity § Example deployment for one gateway • Devices sending one message every 30 minutes • Required 90% success rate • => Maximum number of devices ≃ 27 000 § Maximum number of devices doubled for 4 gateways IoT and Smart Cities samer.lahoud@usj.edu.lb 42
The Challenges
IoT Ecosystem and Business Models IoT and Smart Cities samer.lahoud@usj.edu.lb 44 Device Provider Network Provider Platform Provider Application Provider Application Customer Source: Analysys Mason 2017
IoT Ecosystem and Business Models IoT and Smart Cities samer.lahoud@usj.edu.lb 45 Device Provider Network Provider Platform Provider Application Provider Application Customer 25% 15% 25% 35% Revenue Shares Source: Analysys Mason 2017
IoT Ecosystem and Business Models IoT and Smart Cities samer.lahoud@usj.edu.lb 46 Device Provider Network Provider Platform Provider Application Provider Application Customer 5% 10% 10% 25% EBIT Margin Source: Analysys Mason 2017
The Challenges of IoT for Smart Cities IoT and Smart Cities samer.lahoud@usj.edu.lb 49 Encourage research and innovation in IoT Open market and ensure interoperability Enforce local governance and citizen decision-making

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