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IoT LPWAN Geolocation LoRaWANbringing disruption… Thierry Lestable, Ph.D Director, Head of IoT Business Development & Strategic Partnerships Vice-Chair LoRa Alliance ™

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  • IoT LPWAN Geolocation

    LoRaWAN bringing disruption

    Thierry Lestable, Ph.D Director, Head of IoT Business Development

    & Strategic Partnerships

    Vice-Chair LoRa Alliance

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 2

    Sagemcom brings IoT Tracking Solutions to Life !

    Tracking

    capability is

    THE Key

    Disruptive

    Enabler in IoT,

    fueling

    Innovative

    Marketing

    services!

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 3

    GeoFencing, GeoTargeting, GeoPositioning, Tracking

    Trigger geofences based on events like

    - entering, dwelling, or leaving a place

    - time of day

    - crossing a speed threshold

    - entering a city, state or country

    - after traveling a given distance

    - after a particular change in altitude

    Source: Geoloqi

    Smart Cities

    http://cdn3.raywenderlich.com/wp-content/uploads/2015/02/geofence.png

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 4

    IoT platforms play a critical Role for Business Adoption

    Easy-to-use & Flexible

    Interface to define Geo-

    Fences

    Scenarios & Rules Mgt

    easy to implement

    (Guidance)

    Courtesy of

  • 5 This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 5 This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 6

    Geolocation End-to-End (E2E) Complete Solution Roll-out

    Sagemcom is the ONLY

    player providing End-to-

    End Complete Solution for

    Geolocation:

    - Gateway v2 (Geoloc

    enabled)

    - Location Solver

    (Algorithms processing)

    - LNS API/Metadata (not

    standardized yet by

    Alliance)

    - - Devices with IMU

    Fast, Trustworthy, Reliable E2E Geolocation Roll-out:

    Joint optimization feasible depending on SLA targets

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 7

    Filtering Stop & Go illustration Overall Evaluation Methodology

    Sagemcom has established a whole Evaluation Methodology with system

    Level Dynamic simulators to secure mid/long-term new Algorithms

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 8

    Filtering Illustration, Constant Velocity Models

    i) Reliability of Dynamic Models

    ii) Detection of Model Switching

    iii) Capability to Adapt

    Dyn

    am

    ic M

    ode

    l

    Pro

    ba

    bili

    ty u

    sag

    e

    mobility detected

  • 9 This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 9 This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization

    Chipset

    End Point/Device

    Gateway

    LoRa Network Server (LNS)

    IoT Platform

    Service/Application

    Waste Collection Street Lighting Smart ParkingSmart Build ingSecurity/safety

    Asset Management/Tracking

    Data Analytic Algorithms(incl. Geoloc)

    Smart Agriculture

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 10

    Data Fusion Inertial Measurement Unit (IMU) Part 1 (no GPS)

    Gyroscope

    accelerometer

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 11

    IoT LoRaWAN 1st Generation Siconia Multi-usage Device

    Compatible with all LoRaWAN 1.0

    network Public

    Private

    Private + extension radio partner

    Frequency Unlicensed Band ISM EU, FCC (on-going)

    Multiples sensors for multiple use

    cases Temp, Humidity Acceleration + Gyro Magneto Pressure

    Hardened medium

    -20 C / + 65 C IP65 or more

    JavaScript / application

    NFC interface

    Cases of flexible use 1 product N uses

    Adaptive Form Factor depending

    of requirement (IEC compliancy)

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 12

    IoT LoRaWAN Siconia {GPS/WiFi/BLE/LoRaWAN} Tracking

    Compatible with all LoRaWAN 1.0

    network Public

    Private

    Private + extension radio partner

    Frequency Unlicensed Band ISM EU, FCC (on-going)

    Multiple sensors

    Acceleration Pressure

    Hybrid Positioning:

    GPS /GNSS (incl. Offload) WiFi sniffing BLE Proximity Services LoRa Triangulation

    Hardened medium

    -20 C / + 65 C IP65 or more

    JavaScript / application Cases of flexible use

    1 product/N uses

    Rechargeable battery (micro-usb)

    Adaptive Form Factor depending of requirement (IEC compliancy)

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 13

    Data Fusion IMU GPS Offload Technology Part 2 (with GPS)

    GPS Offloading is outstanding good fit for such IoT LPWAN

    scenarios & power consumption critical constrants!!

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 14

    From Innovation to Disruption Accelerating the IoT Market

    Partner Innovation Program with real

    industrial design Targets

    (Cost , Quality, Time-to-Market efficiency)

    Thanks to Leading Silicon Vendors willing

    to accelerate the IoT LPWAN Market

    Sagemcom will

    circulate (VERY

    SOON) this

    New Generation

    Tracker as a

    Catalyst for

    Asset

    Management/Lo

    gistics, and

    Child/Elderly

    care.

    MAIN Target:

    Disrupt the

    Market!

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 15

    Data Fusion - Map layout (exploitation example)

    Use of OpenStreetMap to get all roads around Sagemcoms HQ

    Black box

    Area requested

    Blue line

    Road

    Green line

    Pedestrian

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 16

    GPS information, machine learning (1/2)

    Fingerprinting usually requires an initial Offline phase, where calibration is

    done for building an initial Radio Map (RSS, TOA, TDOA).

    Then, Machine Learning Algorithms can be used to classify/detect identical

    patterns, and thus identify the Positions.

    Ultimately, Online matching can also be used to adapt/enhance the initial

    dataset/database.

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 17

    GPS information, machine learning (2/2)

    Supervised Learning

    (Calibration phase needed)

    1) K-Nearest Neighbor (k-NN)

    2) Decision Tree (DT)

    3) Neural Networks (NN)

    4) Support Vector Machines

    (SVM)

    5) Bayesian inference

  • 18 This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 18 This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 19

    802.11 channels @2.4GHz 14 channels

    For sake of battery consumption, an Adapted

    Scanning Policy, taking into account Radio

    environment (e.g. Channel Popularity [1,6,11]) is

    likely to improve the battery life. This could be

    adapted by Application Layer.

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 20

    Passive Vs Active Sniffing

    Only 10% additional captured packets via Active sniffing

    In our case, the IoT Device is only using Passing Sniffing,

    for sake of battery consumption.

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 21

    Spectrum Scanning Policy Design

    WiFi Scanning Policy could be configured & driven by cloud requests,

    and/or application (JS)

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 22

    WiFi Sniffing: Database is the KEY (1/4)

    https://developers.google.com/maps/documentation/geolocation/intro

    {

    "homeMobileCountryCode": 310,

    "homeMobileNetworkCode": 410,

    "radioType": "gsm",

    "carrier": "Vodafone",

    "considerIp": "true",

    "cellTowers": [

    // See the Cell Tower Objects section below.

    ],

    "wifiAccessPoints": [

    // See the WiFi Access Point Objects section below.

    ]

    }

    {

    "macAddress": "00:25:9c:cf:1c:ac",

    "signalStrength": -43,

    "age": 0,

    "channel": 11,

    "signalToNoiseRatio": 0

    }

    WiFi sniffing principle is applicable to any database, similar to Google API. Once Location of AP is

    stored, together with their MAC address (Id), then RSSI algorithm can be applied.

    https://developers.google.com/maps/documentation/geolocation/introhttps://developers.google.com/maps/documentation/geolocation/introhttps://developers.google.com/maps/documentation/geolocation/intro#cell_tower_objecthttps://developers.google.com/maps/documentation/geolocation/intro#cell_tower_objecthttps://developers.google.com/maps/documentation/geolocation/intro#cell_tower_objecthttps://developers.google.com/maps/documentation/geolocation/intro#cell_tower_objecthttps://developers.google.com/maps/documentation/geolocation/intro#wifi_access_point_objecthttps://developers.google.com/maps/documentation/geolocation/intro#wifi_access_point_objecthttps://developers.google.com/maps/documentation/geolocation/intro#wifi_access_point_objecthttps://developers.google.com/maps/documentation/geolocation/intro#wifi_access_point_object

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 23

    WiFi Sniffing: Database is the KEY (2/4)

    {

    "considerIp": "false",

    "wifiAccessPoints": [

    {

    "macAddress": "00:25:9c:cf:1c:ac",

    "signalStrength": -43,

    "signalToNoiseRatio": 0

    },

    {

    "macAddress": "00:25:9c:cf:1c:ad",

    "signalStrength": -55,

    "signalToNoiseRatio": 0

    }

    ]

    }

    {

    "location": {

    "lat": 51.0,

    "lng": -0.1

    },

    "accuracy": 1200.4

    }

    Example of request towards API, with device seen

    from 2 Access Points

    AP#1

    AP#2

    Example of Geoloc result/answer

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 24

    WiFi Sniffing: Database is the KEY (3/4)

    http://hotspots.wifi.comcast.com/

    http://wifi.xfinity.com/default.php#find-a-hotspot

    Clearly, COMCAST

    could have the

    relevant Database

    information, through

    its Xfinity Wifi

    service.

    http://hotspots.wifi.comcast.com/http://hotspots.wifi.comcast.com/http://wifi.xfinity.com/default.php#find-a-hotspothttp://wifi.xfinity.com/default.php#find-a-hotspothttp://wifi.xfinity.com/default.php#find-a-hotspothttp://wifi.xfinity.com/default.php#find-a-hotspothttp://wifi.xfinity.com/default.php#find-a-hotspothttp://wifi.xfinity.com/default.php#find-a-hotspot

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 25

    WiFi Sniffing: Database (& community) is the KEY (4/4)

    https://wigle.net/

    https://location.services.mozilla.com/

    https://wigle.net/https://wigle.net/https://location.services.mozilla.com/https://location.services.mozilla.com/

  • This document and the information contained are Sagemcom property and shall not be copied or disclosed to any third party without Sagemcom prior written authorization 26

    Finally.

    Sagemcom is deeply committed to make IoT LPWAN Asset

    Management/Tracking a Business reality.

    LoRaWAN via its inherited Time stamping capabilities from

    CSS, together with Very Low Power & High Range

    takes a definitely a Key Disruptive position in that Market.

    Combining with other IoT Technologies such as GPS Offload,

    WiFi scanning and BLE secures a strong Leaders Position.

    This is a joint Optimization Problem from the Device towards

    Cloud Processing/Data Analytics & Anchors positions

    Databases, via Gateways.

  • Thanks for your interest

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