performance analysis of a user-centric crowd-sensing water ... · performance analysis of a...

Nikolaos Rapousis and Maria Papadopouli

UNIVERSITY OF CRETE Department of Computer Science

Department of Computer Science, University of Crete Institute of Computer Science, Foundation for Research & Technology – Hellas (FORTH)

http://www.ics.forth.gr/mobile

Speaker: Nancy Panousopoulou

This research has been funded by a GSRT Research Excellence grant (2012-2015), a Google Faculty Award (2013-2014), and EU Hydrobionets

13-Apr-2015 CySWater 1

Performance Analysis of a User-centric Crowd-sensing Water Quality Assessment System

http://www.ics.forth.gr/mobile

Resources WHH-WASH Sector Report, FAO, WHO, UN

CySWater 3 13-Apr-2015

Roadmap

• Introduction & Motivation

• Related work

• QoWater system

• Proof-of-concept & pilot testbed

• Preliminary field study & evaluation results

• Conclusions and future work


Contamination events

• Pressure loss or change may result in backflow incidents during which contaminated soil water enters the water distribution network (WDN) through pipe breaks or leaking joints

• Corrosion of iron, copper, and lead parts of the WDN (e.g., due to free chlorine for disinfection)

• Bioterrorism

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Motivation • Efficient monitoring & management of the infrastructure, including the last-mile access

network

• User in the loop: user engagement

• Increased customer awareness about the water quality & querying mechanisms

• Fast & efficient warning/alerting in the case of contamination

• More accurate models for assessing the quality of the water


Roadmap

• Introduction & Motivation

• Related work

• QoWater

• Proof-of-concept

• Evaluation

• Conclusions and future work


Related activities in water contamination

1. Mobile apps for querying specific sensors & providing feedback (e.g., [Jonoski13], Delhi Jar board, 311)

2. Sensor placement for supporting warming systems, e.g., [TriopuNet12, Pelerman15, Krause08]

3. Detection algorithms for drinking water contamination, e.g., [Whelston’07, Dietrich’14, Mix12]


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4/20/2016 CYSWATER 10

Roadmap

• Introduction

• Related work

• QoWater system

• Proof-of-concept

• Evaluation

• Conclusions future work


Health Organization sensors

Citizens/Customers with QoWater client

Water Distribution Network

QoWater client

QoWater server

Regulators, administrators, scientists

sensors

sensors

QoWater system: client-to-server architecture

QoWater clients on mobile devices

• Collect customer/scientist sentiments & store them locally

• Upload data to the QoWater server

• Query the QoWater server to acquire quality related info for various regions

QoWater server

• Collects client and sensor data in spatio-temporal geo-DB

• Responds to queries sent by users, providers & regulators


Sensor measurements pH, temperature, conductivity oxidation-reduction potential & Ion Chlorine

Main screen


Query based on clients score or sensor measurements

Results for query area, based on clients option eg, customer score


Registration form for the Customer role

Registration form for the Scientist role



Color: red/brown, green/blue, white, black Taste: bitter, salty, sweet Odor: sewer, chlorine, gasoline, chemical Appearance: floating particles, sand, milky, rusty, stain, animal, plant Pressure: no water, low, high Photo: required if Appearance problem exist


Taste: bitter, salty, sweet Odor: sewer, chlorine, gasoline, chemical Appearance: floating particles, sand, milky, rusty, stain, animal, plant Pressure: no water, low, high

Chemical: turbidity, Br, Cl, Na, K, Mg2, biochemical oxygen demand, acidity, disssolved oxygen, etc Biological: ephemeroptera, plecoptera, excherichia coli, coliform bacteria, etc

QoWater Architecture QoWater server

Secure sensor readings upload

Certificate Manager

Memcached service

Certificate Authority

Data receiver

Query handler

Access control

geoDB

Event detector

Data validator

Analyzer

HTTP service

PHP application

Upload data

QoWater sensor node

Broadcast sensor readings

Monitor

Temperature

Conductivity

ORP

PH

Chlorine ions

Back-end interface

WiFi interface

QoWater client

Android device

Po

siti

on

Qu

erie

s

Save

dat

a

Data Recorder

Cu

sto

mer

Fo

rm

Scie

nti

st

Form

Qu

eryi

ng

GUI

Sensor reading

GPS

Camera

Feedback

CSV

Measurement location

Back-end interface

Save sensor readings

SQLite


QoWater server

Secure sensor readings upload

Certificate Manager

Memcached service

Certificate Authority

Data receiver

Query handler

Access control

geoDB

Event detector

Data validator

Analyzer

HTTP service

PHP application

Upload data

QoWater sensor node

Broadcast sensor readings

Monitor

Temperature

Conductivity

ORP

PH

Chlorine ions

Back-end interface

WiFi interface

QoWater client

Android device

Po

siti

on

Qu

erie

s

Save

dat

a

Data Recorder

Cu

sto

mer

Fo

rm

Scie

nti

st

Form

Qu

eryi

ng

GUI

Sensor reading

GPS

Camera

Feedback

CSV

Measurement location

Back-end interface

Save sensor readings

SQLite


Rely on the end-to-end security that protects the integrity & confidentiality by leveraging standard technologies (eg public-private key pairs, TLS)

Use Hadoop Distributed FS & Hbase for higher aggregate I/O throughput

Preliminary field study

Three sources of drinking water: tap, purified, bottled

Objective measurements by sensor node • Duration of sampling: 36 minutes • One data point every 10 seconds • Collection of 215 data points (omit the first 50 data points)

Subjective measurements (QoE score) by 44 subjects • Three cups containing tap, purified & bottled water with no indication of the source of the water • Each subject inspects, smells, tastes the water from each cup and provides its score immediately


QoWater Testbed Sensor • with a micro-controller that operates at 14MHz frequency • 8 KB RAM memory, 2 GB SD card • IEEE802.11b/g WiFi

Server • VM with 2 cores at 2.4 GHz • 4 GB RAM, 27 GB storage • Ubuntu 14.04 OS

Client • Android 2.1 OS • 512 MB RAM • 3.7 inches (480 x 800)


Emulated QoWater clients • VM with 12 cores at 2.4 GHz • 32 GB RAM, 150 GB storage • Windows7

Scenario Step QoWater

Uploading QoWater Querying

QoWater Client-Sensor

U-map Querying

U-map Uploading

Skype Call

YouTube Streaming

1 Unlock phone Unlock phone Unlock phone Unlock phone Unlock phone Call a contact Unlock phone

2 Launch QoWater Launch QoWater Launch QoWater

Launch u-map

Launch u-map

Call duration 20 sec

Launch YouTube

3 Tap Sentiment Tap Search Tap Sensor Tap Upload data

Tap Select Operator

N/A Display 78 sec video

4 Fill complaint form

Retrieve user location

Display 35 sec sensor measurements

Upload 4.8 MB data

Tap Polygon N/A Return to Home Screen

5 Fill 5 star QoE Tap Query Area Return to Home Screen

N/A Tap Submit N/A N/A

6 Upload 1.5 MB data

Display response N/A N/A Display response

N/A N/A

7 Return to Home Screen

Return to Home Screen

N/A N/A Return to Home Screen

N/A N/A

Evaluating: Response Delay Testbed

QoWater client (Android)

QoWater server

T1

T2

T5

T6

T3

T4

Query

Display

Response generation

time

AP

internet

Android Delay Network Delay

Server Delay

Network Delay Android Delay

QoW client (Android)

QoW server

T2

T6

T4

Query

Display

Response generation

time

AP Internet

T1

T5

T3

Evaluating: Response Delay Testbed (2)

Response Delay

Scenario Android/Waspmote Server Network Total (ms)

QoWater: Uploading 393 (52) 69 (5) 249 (47) 711

QoWater: Querying 102 (19) 1451 (83) 262 (66) 1815

QoWater: Sensor 4000 (233) 32 (1) 4000 (500) 8023

U-map: Uploading 49 (N/A) 159 (N/A) 379 (N/A) 587

U-map: Querying 43 (N/A) 135 (N/A) 8 (N/A) 186

• Each scenario was executed 20 times • QoWater sensor uploading is the most time consuming (background does not effect response) • Note that u-map users different dataset size and response processing

Power Consumption

Start AppScope

End AppScope

Launch application

AppScope Inter Process Communication

Execute scenario

Exit application

Start AppScope

End AppScope

Collect measurements

Create report

• AppScope for the energy measurements • QoWater client is an HTC Nexus One smartphone • Compare the QoWater with the u-map & popular apps (e.g., Skype, YouTube)

Power Consumption (con’td)

Scenario CPU Display GPS WiFi Total (mW)

QoWater: Uploading 68 (14) 712 (10) 17 (1) 23 (7) 803 820

QoWater: Querying 56 (3) 548 (15) 17 (1) 8 (3) 612 629

QoWater: Sensor 4 (1) 767 (10) 0 1 (0) 772

U-map: Uploading 35 (23) 567 (1) 0 88 (14) 690

U-map: Querying 33 (3) 563 (15) 0 6 (4) 770

YouTube: Video 23 (3) 786 (5) 0 6 (4) 815

Skype: Call 111 (14) 639 (15) 0 57 (20) 807

Suspended: 3 (1) 0 0 6 (3) 9

• 100 repetitions of each scenario • The 3G has been omitted • Display is the most energy demanding in all scenarios

Scalability

Response Delay

Served vs. Time-out

V-Trickle vs Periodic

V-Trickle extends the battery lifetime approximately 4 times

Conclusions

• The QoWater is a monitoring & querying mechanism that can engage citizens, improve the transparency of the monitoring process and provide alerts in case of contamination events

• Relatively low response delay and power consumption • Most demanding scenario consumes less than a 20 sec Skype call • Current server cannot adequately support large-scale regions – possible solutions through

cloud computing • Preliminary earlier field study indicates that users can distinguish different sources of water


Future work

• Analysis of the user sensitivity regarding the water quality • Prediction models of contamination events based on extensive field studies • Analysis of the impact of incentives to enhance the participation of citizens on systems

adoption


4/20/2016 CYSWATER 33

Questions

performance analysis of a user-centric crowd-sensing water ... · performance analysis of a...

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