NOMBRE DEL BECARIO Liu Cheng, Alexander Technische Universität München

258 Pages·2015·12.85 MB·English

PROGRAMA DE BECAS " UNIVERSIDADES DE EXCELENCIA POSTGRADO"
NOMBRE DEL BECARIO Liu Cheng, Alexander
Technische Universität München
UNIVERSIDAD
(Universidad Técnica de Munich)
Máster de Ciencias / Master of Science
(M.Sc.),
TITULO OBTENIDO Advanced Construction and Building
Technology—Automation, Robotics,
Services
Diseño e implementación de un sistema
nuevo y económico de detección de
caídas y de intervención basado en
tecnologías de redes de sensores
inalámbricos para una vida
independiente [enfocado en personas de
tercera edad].

Design and Implementation of a Novel
Cost-effective Fall-Detection and -
TEMA DE TESIS
Intervention System for Independent
Living based on Wireless Sensor
Network Technologies.

Entwurf und Implementierung eines
neuartigen kostengünstigen
Sturzerkennungs- und
Interventionssystems für
selbstbestimmtes Leben, basierend auf
drahtloser Sensornetzwerktechnologien
FAKULTÄT FÜR ARCHITEKTUR

Lehrstuhl für Baurealisierung und Baurobotik

DER TECHNISCHEN UNIVERSITÄT MÜNCHEN

Master of Science Thesis in
Advanced Construction and Building Technology

Design and Implementation of a Novel Cost-
effective Fall-Detection and -Intervention System
for Independent Living based on Wireless Sensor
Network Technologies

Alexander LIU CHENG
FAKULTÄT FÜR ARCHITEKTUR

Lehrstuhl für Baurealisierung und Baurobotik

DER TECHNISCHEN UNIVERSITÄT MÜNCHEN

Master of Science Thesis in
Advanced Construction and Building Technology

Entwurf und Implementierung eines neuartigen
kostengünstigen Sturzerkennungs- und
Interventionssystems für selbstbestimmtes Leben,
basierend auf drahtloser
Sensornetzwerktechnologien

Author: Alexander LIU CHENG
Supervisor: Prof. Dr.-Ing. Thomas BOCK
Advisor: Dr.-Ing. Christos GEORGOULAS
Date: August 12, 2015
Ich versichere, dass ich diese Masterarbeit selbständig verfasst und nur die angegebenen
Quellen und Hilfsmittel verwendet habe.

München, den 12 August 2015 Alexander LIU CHENG
i
Acknowledgments

The present work would not have been possible without the guidance, patience, and
perseverance of my Supervisor, Prof. Dr.-Ing. Thomas BOCK and my Advisor, Dr.-Ing.
Christos GEORGOULAS. One would be hard-pressed to find a more stimulating, engaging,
and inspiring dynamic duo who steer by leading and not by pushing.

I also acknowledge Mr. Andreas BITTNER, the Mechatronics and Systems Administrator at
the laboratory of our Lehrstuhl für Baurealisierung und Baurobotik for his generous technical
assistance and formidable expertise.

Finally, I acknowledge The Secretariat for Higher Education, Science, Technology and
Innovation of Ecuador for having supported me and my work for the past two years.
ii
Dedication

To my forbearing family.
iii
Abstract

The present thesis details the design and implementation of a novel cost-effective Fall-
Detection and -Intervention System (FaDIS) based on Wireless Sensor Network (WSN)
technologies. The system is designed to integrate seamlessly into existing Ambient Assisted
Living environments to create a versatile yet robust de facto Cyber-Physical Network (CPN),
where software and hardware devices and agents attempt to facilitate a safe and proactive
independent living. FaDIS is designed to operate both as an add-on component to existing
centralized solutions—complete or otherwise—or as an integral yet independent component
of decentralized, scalable, and expandable solutions. FaDIS is developed and implemented in
two parts—each with different Technology Readiness Levels (TRLs)—where the first lays the
foundations of the system in the centralized context, and where the second expands on the
first to satisfy the expectations and to exploit the advantages of a decentralized context. One
the one hand, Part 1 is developed as a scaled proof-of-concept that uses a multi-point network
protocol, where the existing environment’s central computer serves as the system-node (i.e.,
the sink node), and where a low-cost laser is used together with Light Dependent Resistors
(LDRs) in a predefined environment to gauge the probabilities of an emergency-event based
on the correlation between object-detection instances and user-generated gyroscopic and
accelerometer data. On the other hand, Part 2 (TRL 5-7) is developed as a fully operational,
real-scale implementation that uses a self-healing mesh network protocol, where its own
BeagleBone Black (BBB) development platform—which is completely independent from any
preexisting central computer—serves as the sink node, and where two Class 2M 10º line
lasers are used together with LDRs in a non-predefined environment—whose extents are
ascertained via self-calibration routines—to gauge the probabilities of an emergency-event
based on the estimated dimensions of the collapsed object (as anticipated by the number of
instantiated direct laser vs. reflected laser intersections). In both Parts 1 and 2, if FaDIS
construes the probabilities of an emergency event as high, the same series of corresponding
robotic response-actions intervene locally while Internet of Things (IoT) notifications are sent
to emergency-personnel, care-takers, and/or family-members via both wireless and cellular
technology globally. A series of sample runs are detailed and described in the present work in
order to demonstrate and to argue for the feasibility and functionality of FaDIS.
iv
Outline of the Thesis

CHAPTER 1: Introduction
This chapter begins with overview and a discussion of the motivations behind
Ambient Intelligence (AmI) and Ambient Assisted Living (AAL) with respect to
Activities of Daily Living (ADLs)—with particular thematic emphasis on
sensing as well as present high-costs. The Purpose and Objectives of the present
work—including its scale, scope, and contribution—as well as the
corresponding Impacts are then stated and described.

CHAPTER 2: State of the Art
This chapter discusses the state of and justifies the emphasis on the following
comprehensive sensing-and-actuating systems, which emerging trends suggest
to be the particularly promising for the fields of AmI and AAL: Wireless Sensor
Networks (WSNs), Cyber-Physical Networks (CPNs), and Body Area Networks
(BANs). The chapter will end with a brief discussion of the potential integration
of BANs.

CHAPTER 3: Concept, Methodological Approach, and Implementation
This chapter describes the concept, outlines as well as justifies the
methodological approach, and details the step-by-step implementation of FaDIS
in Parts 1 and 2 in exhaustive detail. The chapter ends by considering optional
components that may be added to the modules built in Parts 1 and 2 in order to
enhance FaDIS’s functionality.

CHAPTER 4: Discussion of Results
This chapter provides an overview of the results obtained from a series of six
sample runs or demonstrations, with the objective of experimentally proving the
feasibility and functionality of FaDIS.

CHAPTER 5: Conclusions, Limitations, and Future Development
This chapter reflects upon the performance of FaDIS, its present limitations, and
corresponding future development in light of the former two.
v

Table of Contents

Acknowledgments ....................................................................................................................... i 
Dedication................................................................................................................................... ii 
Abstract ..................................................................................................................................... iii 
Outline of the Thesis ................................................................................................................. iv 
1  Introduction ........................................................................................................................ 1 
1.1  Objectives .................................................................................................................... 3 
1.2  Impact .......................................................................................................................... 4 
2  State of the Art ................................................................................................................... 6 
2.1  Wireless Sensor Networks (WSNs) ............................................................................. 6 
2.2  Cyber-Physical Networks (CPNs) ............................................................................. 10 
2.3  Body Area Networks (BANs) .................................................................................... 16 
3  Concept, Methodological Approach, and Implementation .............................................. 20 
3.1  Part 1 (TRL 3-4): Proof-of-Concept Implementation of Fall-Detection and -
Intervention System (FaDIS) based on Laser-Reflectivity Localization and Robotic
Assistance .................................................................................................................. 20 
3.1.1  Step 1: Design and Development of Laser-localization Modules A and B ....... 24 
3.1.2  Step 2: Monitoring and Recording of User Activity data via Module C and
Apple’s iPhone 4. ............................................................................................... 29 
3.1.3  Step 3: Correlating laser-localization results with monitored activity data to
trigger Robotic and Automated Intervention Solutions via Modules D and E .. 33 
3.2  Part 2 (TRL 5-7): Fully Operational and Real-Scale Implementation of the Fall-
Detection and -Intervention System (FaDIS) ............................................................. 50 
3.2.1  Step 1: BeagleBone Black Revision C Initial Configuration and Setup ............. 60 
3.2.2  Step 2: Creating a network mesh of BeagleBone Black Nodes .......................... 64 
3.2.3  Step 3: Setting up the deployment context: BR2’s Bathroom ........................... 70 
3.2.4  Step 4: Design and Development of Laser-localization Module A .................... 73 
3.2.5  Step 5: Design and Development of Laser-localization Module B .................... 83 
3.2.6  Step 6: Description of Initialization, Calibration, and Detection Routines ........ 90 
3.3  Additional and Optional Components ..................................................................... 117 
4  Discussion of Results ..................................................................................................... 121
vi
4.1  Initialization and First run: Calibration and Detection of “No Objects” ................. 121 
4.2  Detection of “Small Object” .................................................................................... 127 
4.3  Detection of “Large Object” .................................................................................... 131 
4.4  Detection of “Very Large Object” (variation 1) ...................................................... 135 
4.5  Detection of “Very Large Object” (variation 2) ...................................................... 140 
4.6  Detection of “Very Large Object” (variation 3) ...................................................... 145 
5  Conclusions, Limitations, and Future Development ...................................................... 152 
Bibliography ........................................................................................................................... 161 
List of Figures ........................................................................................................................ 170 
List of Tables .......................................................................................................................... 176 
List of Abbreviations .............................................................................................................. 177 
Appendices ............................................................................................................................. 180 
Appendix A: Part 1—Arduino code for sending SMS messages via Siemens TC35 GSM
shield ........................................................................................................................ 180 
Appendix B: Part 1—Arduino code for sending SMS messages via Arduino Wi-Fi shield,
Twilio, and Temboo ................................................................................................. 181 
Appendix C: Part 1—Arduino code for sending Email messages via Arduino Wi-Fi shield,
Gmail, and Temboo .................................................................................................. 183 
Appendix D: Part 1—Arduino code for requesting data statistics from Fitbit ................... 185 
Appendix E: Part 2—BBB Coordinator system-node, with a local Infrared sensor,
broadcasting its sensor data and receiving that of others in a network mesh streaming
to Plotly .................................................................................................................... 187 
Appendix F: Part 2—BBB Router system-node, with a local Temperature and Humidity
sensor, broadcasting its sensor data and receiving that of others in a network mesh
streaming to Plotly ................................................................................................... 191 
Appendix G: Part 2—BBB End Device system-node, with a local Light Dependent Resistor
sensor, broadcasting its sensor data and receiving that of others in a network mesh
streaming to Plotly ................................................................................................... 196 
Appendix H: Part 2—Arduino program for Module A—Laser module ............................. 201 
Appendix I: Part 2—Arduino program for Module B—LDRs module ............................... 214 
Appendix J: Part 2—Python program for Coordinator BBB system-node ....................... 217 
Appendix L: Part 2—FaDIS: Sample Operation Log ........................................................ 221 
I.  Initialization and First run: Calibration and Detection of “No Objects” .......... 221 
II.  Detection of “Small Object” ............................................................................ 227 
III.  Detection of “Large object” ............................................................................. 231