Developing Analytics and Deploying IoT Systems

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Developing Analytics and Deploying IoT Systems Amit Doshi Senior Application Engineer, MathWorks India amit.doshi@mathworks.in 2015 The MathWorks, Inc. 1

What is Internet of things (IoT)? Internet of Things (IoT) is internetworking of a large number of embedded devices ( things ) which are connected to the Internet. These connected devices communicate with people and other things and often provide sensor data to cloud storage and cloud computing resources where the data is processed and analyzed to gain important insights. Why now Cheap cloud computing power and Increased device connectivity More comfort, convenience, performance, increased safety, low risk etc. 2

Chips in everything & the rise of Ubiquitous sensing Extracting insights from sensor data a common practice Human Applications: Medical Leasure Sports/Fitness Military Social Retail Security 3

Example BuildingIQ Cloud based adaptive building energy management Challenge Minimize energy costs of large-scale commercial buildings without compromising tenants comfort. Solution Develop cloud based realtime adaptive system via proactive, predictive optimization algorithm.

Real-time, closed-loop optimization algorithms DATA - Billions of data points: Physics, energy cost, power, internal temperatures, ambient temperatures, ambient humidity, building operation schedule, comfort bounds, etc. Geographically distributed Sensors Analytics and Machine Learning plus system identification, control theory & more Geographically distributed Sensors Predictive Model deployed on cloud with client system and real-time data feeds Current energy costs & demand Weather Feeds 5

Example BuildingIQ Cloud based adaptive building energy management After: 25% cost reduction Before 6

High Level Architectural View of Internet of Things Communications Network Data Aggregation & Analytics Deploy analytics to server/cloud Deploy algorithms to nodes/devices Smart Connected Devices Algorithm Development Sensor Analytics 7

IoT Challenges Need variety of data for analysis. How to get started? Communications Network Multi- Disciplinary Workflow Data Aggregation & Analytics Need IT expertise to integrate analytics on cloud. Can I prototype my IoT solution first? Deploy analytics to server/cloud Smart Connected Devices How do I deploy my algorithms on a smart device / cloud? Deploy algorithms to nodes/devices Algorithm Development Sensor Analytics Predictive algorithm? Do I need to be Data Scientist? 8

How MathWorks Addresses IoT Challenges? MATLAB makes it easy to acquire both business and engineering data 1 3 Communications Network 4 Smart Connected Devices Data Aggregation & Analytics Deploying applications that run on both traditional IT and embedded platforms Deploy algorithms to nodes/devices Deploy analytics to server/cloud Algorithm Development Sensor Analytics Provides a platform for prototyping IoT systems or small scale deployment with no web infrastructure needed 2 Enable Domain Experts to be Data Scientists 9

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Examples for Today Data acquisition from edge nodes and analysis using MATLAB Measure, explore, discover weather patterns Develop analytics using MATLAB and deploy as a web service Forecast wind driven tide levels Develop analytics using MATLAB and deploy on a smart device Human Activity Analysis and Classification Develop analytics using MATLAB and optimal partition it on an edge device and cloud Smart traffic monitoring using Raspberry Pi webcam 11

Get Started with IoT by Accessing Sensor Data in MATLAB Analog Input Serial Port TCP/IP UDP [data, time] = StartForeground(s); s1 = serial( COM1 ); I = i2c( aardvark, 0, Hex2dec( 50 ) A = fread (obj); t = tcpip ( localhost, 30000, NetworkRole, server ); fread (t, 10) Prototyping is an important step in developing IoT system. You need only a sensor and MATLAB to get started 12

Example 1: Weather monitoring using ThingSpeak and MATLAB It s hot out!! Don t forget to carry a bottle of water 13

What Is ThingSpeak? Web Site For People Web Service for Devices 14

ThingSpeak New MathWorks web service hosted on AWS Lets you collect, analyze and act on data from things such as Arduino, Raspberry Pi, BeagleBone Black, and other hardware Over 130,000 users worldwide It has MATLAB for IoT Analytics https://thingspeak.com 15

Example 1: Weather monitoring using ThingSpeak and MATLAB 16

Example 1: Weather monitoring using ThingSpeak and MATLAB Data Aggregation Data Analysis Editing algorithm on cloud is very easy as it s running MATLAB 17

Examples for Today Data acquisition from edge nodes and analysis using MATLAB Measure, explore, discover weather patterns Develop analytics using MATLAB and deploy as a web service Forecast wind driven tide levels Develop analytics using MATLAB and deploy on a smart device Human Activity Analysis and Classification Develop analytics using MATLAB and optimal partition it on an edge device and cloud Smart traffic monitoring using Raspberry Pi webcam 18

Example 2: Low Tide Prediction Using MATLAB And ThingSpeak Challenge Boats get stuck in mud at low tide Solution Advance notification of low tide Even cooler to get notifications on mobile 19

Example 2: Low Tide Prediction - Approach Access and Explore Data Preprocess Data Develop Predictive Models Integrate Analytics with Systems Files Working with Messy Data Model Creation e.g. Machine Learning Desktop Apps Databases Data Reduction/ Transformation Parameter Optimization Enterprise Scale Systems Sensors Feature Extraction Model Validation Embedded Devices and Hardware 20

Example 2: Low Tide Prediction Using MATLAB And ThingSpeak 21

Learn Further: Which Toolboxes Work in ThingSpeak? Statistics and Machine Learning Toolbox Curve Fitting Toolbox Control System Toolbox Signal Processing Toolbox Mapping Toolbox System Identification Toolbox Neural Network Toolbox DSP System Toolbox Datafeed Toolbox Financial Toolbox 22

Examples for Today Data acquisition from edge nodes and analysis using MATLAB Measure, explore, discover weather patterns Develop analytics using MATLAB and deploy as a web service Forecast wind driven tide levels Develop analytics using MATLAB and deploy on a smart device Human Activity Analysis and Classification Develop analytics using MATLAB and optimal partition it on an edge device and cloud Smart traffic monitoring using Raspberry Pi webcam 23

Example 3: Sensor Analytics and Development of Smart Connected Devices Feature Extraction Classification 24

Example 3: Sensor Analytics and Development of Smart Connected Devices - workflow Connect and Acquire Signal Processing Machine Learning Embedded Implementation 25

Example 3: Sensor Analytics and Development of Smart Connected Devices - Workflow Connect and Acquire 1 26

Example 3: Sensor Analytics and Development of Smart Connected Devices - Workflow Signal Processing and feature extraction 2 27

Example 3: Sensor Analytics and Development of Smart Connected Devices - Workflow Machine Learning 3 28

Example 3: Sensor Analytics and Development of Smart Connected Devices - Workflow Embedded Implementation 4 29

Example 3: Sensor Analytics and Development of Smart Connected Devices - Workflow App in action 30

Example 3: Summary of Sensor Analytics Development and Deployment Connect and Acquire Signal Processing Machine Learning Embedded Implementation 31

Code Generation using MathWorks Product Embedded Coder generated C code that was error-free and efficient so much so that the team only needed to write code for our device drivers. This saved us 6 months of development time. - Dr. Christian Robl, System Architect at Vodafone Group R&D. 32

Examples for Today Data acquisition from edge nodes and analysis using MATLAB Measure, explore, discover weather patterns Develop analytics using MATLAB and deploy as a web service Forecast wind driven tide levels Develop analytics using MATLAB and deploy on a smart device Human Activity Analysis and Classification Develop analytics using MATLAB and optimal partition it on an edge device and cloud Smart traffic monitoring using Raspberry Pi webcam 33

Example 4: Traffic monitoring can be used for smart traffic light management 34

Example 4: Traffic Monitoring Objectives Measure, explore, discover traffic patterns Provide live local traffic information service Solution RaspberryPi + webcam Automated deployment of vision algorithms on embedded sensor Full example available at makerzone.mathworks.com Cloud needs only car count and not all video data 35

Example 4: Traffic Monitoring - Approach Step 1: Prototyping Create a prototype in Simulink and develop a logic Just Simulink and a camera feed Car count Historical Video feed 36

Example 4: Traffic Monitoring - Approach Step 2: Port it to Raspberry Pi Use the code generation capabilities of Simulink to deploy this algorithm onto the Raspberry Pi Car count 37

From Data to Insight When should I start for home? Well, I better start early from office or stay back late in the office 38

Example 4: Summary Developing smart devices Step 1: Prototyping Create a prototype in Simulink and develop a logic and send count to cloud Need only Simulink and a camera feed to start with Step 2: Port it to Raspberry Pi Use the code generation capabilities of Simulink to deploy this algorithm onto the Raspberry Pi 39

ThingSpeak for Small Scale Deployment External Data & Business Systems Ingest Store Compute Deploy analytics To cloud Smart Connected Devices Algorithm Development Sensor Analytics 40

Integrating MATLAB with Third Party IoT Cloud Platforms IoT Platform External Data & Business Systems Ingest Store Compute MATLAB Production Server Deploy analytics To cloud Gateway Smart Connected Devices Algorithm Development Sensor Analytics Algorithm Development 41

Integrating MATLAB in Large Scale Production Systems Data Analytics Business System Databases Visualization Cloud Storage Azure Blob Azure SQL MATLAB Production Server Web Request Broker IoT Custom App Public Cloud Platform Private Cloud 42

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MathWorks Addresses IoT Challenges Quickly collect and analyze IoT data with ThingSpeak and MATLAB Develop analytics algorithms using MATLAB and toolboxes Deploy on smart devices using code generation and embedded target support Deploy on cloud using ThingSpeak and MATLAB Production Server 44

What You Can Do to Learn More Log-in to ThingSpeak with you MathWorks account and explore View a webinar on Machine Learning with MATLAB Read a Technical Article on Forecasting Tides with MATLAB Read a tutorial on how to send data to ThingSpeak over MQTT 45

MathWorks Training Offerings http://www.mathworks.com/services/training/ 46

Speaker Details Email: amit.doshi@mathworks.in LinkedIn: https://in.linkedin.com/in/amit-doshi Contact MathWorks India Products/Training Enquiry Booth Call: 080-6632-6000 Email: info@mathworks.in Your feedback is valued. Please complete the feedback form provided to you. 47