Big data and IoT technologies are increasingly being used together for new applications. The document discusses using big data and IoT for tourism recommendations in Oman. It outlines a case study approach involving collecting hotel review data from TripAdvisor, analyzing the data using sentiment analysis and topic modeling, and developing a recommendation system. The system would integrate IoT devices in hotel rooms to gather additional guest feedback and preferences on amenities like lighting, music, and more. This combined big data and IoT approach aims to provide more personalized recommendations to improve the Omani tourism experience.

1. BIG + IOT FOR IDEAS
A Case Study Approach
Sharjeel Imtiaz | PhD Data Science – last stage | University of East London, UK

2. Big Data Definition
• Any piece of information can be considered as data.
• This data can be in various forms and in various sizes. It can vary from
small data to very big Data.
• Any data that can reside in RAM or memory is considered as small data.
Small data is less than 10s of GBs.
• Any data that can reside in Hard Disk is considered as medium data.
Medium data is in the range of 10s to 1000s of GBs.
• Any data which cannot reside in Hard disk or in a single system is
considered as Big Data. Its size is more than 1000s of GBs.

3. Trends?

4. How to process Big Data
To process and manage such huge volume
of data, different Big Data technologies
come into picture. It is a new data
challenge that requires leveraging
existing systems differently as some time
ago, data type and volume were not of the
type as it is today.

5. Big data reveals Shakespeare co-authored 17 of his
plays (A English Literature Domain- NLP)
• To process and manage such huge
volume of data, different Big Data
technologies come into picture.
• It is a new data challenge that
requires leveraging existing
systems differently as some time
ago, data type and volume were
not of the type as it is today.
• He said that it remains unclear
exactly how the authors worked
together. It could have been that
Marlowe wrote the texts and
Shakespeare later edited them.
We counted how often particular words and
phrases appeared in texts by Shakespeare and
other authors of his day. These patterns were
pretty unmistakable," researcher Gabriel Egan of
De Montfort University in Leicester told news
agency dpa.
Marlowe wrote the texts and Shakespeare later
edited them. (May be)

6. Sentiment Analysis with Topic Modeling –
(A COMPUTER SCIENCE DOMAIN)
• What are aspect of particular domain like Hotel have different aspect
Service, cleanliness , room, location, and 7 more ….
• A product in amazon is having many product features price, and other
• A stock market product is having many features and aspect basedOn
tweeter
• Disaster alerts data from tweeter is having aspects.
Sentiment analysis of
aspect in Review is
challenge and trend…..

7. IOT WITH BIG DATA INFRASTRUCTURE
.The ideal architecture connect devices to data
Analytics
. Security IOT based devices that monitor all
Type of network security attacks
. IOT device that monitor the network traffic and
Avoid congestion with auto monitoring and
Avoidance mechanism
• Disaster monitoring and alert mechanism
for big data analytics)

8. Engineering Good Topics (Good for Oman)
The solar panel produces the
Current due to the hitting of the
photons from the sun on the
silicon atoms.
Or Layman
Thus in simple words, SUNLIGHT
FALLS ON THE SOLAR PANEL
AND CURRENT is produced
Example for 100 watts pannel, Voc=20V or 21V and Isc=5 A thus
P=100 watts (approx) ---( How to manage it efficiently)

9. Why Cloud
• Cloud process big data volume and process in parallel nodes
framework and provide Machine Learning library.
• It is not possible to process data in Machine learning model like Neural
network on single machine within few second or a minute
More features more
processing

10. IOT TO BIG Data to Analytics
• Integrated IOT with big data is not the easy required domain knowledge
• Amazon Domain products data &
• category
• Tweets data
• Social media data
Tools SPSS is not for Big
data and not so good
WEKA, RMiner.
R + Python + RStudio +
Cloud based ML

11. What is your network architecture?

12. Architecture
IOT of network security or health or
tourism devices with Big data
BIG DATA WITH IOT IS TREND

13. OUR IOT RECOMMENDATION SYSTEM FOR
OMAN TOURISM (IOT + BIG DATA)

14. IOT Recommendation system for Oman Tourism
A Case study with process of Data Science and
Computations
Step 1&2&3: Data Collection + Preparation
+ storage
Data Collection
Data
Preparation
Storage &
Structure on
Hadoop (HDFS)
Data Exploration
Sentiment
Analysis
Model Analysis
with Hadoop

15. TRC funding Project – Trip advisor Web Site
scraping Tool
• TripAdvisor is the most well-known customer for reviewing
website for hotels and restaurants in Spain, although
Yelp.com is more popular on a global scale.
• TripAdvisor users can write reviews and post scores from 1
(“terrible”) to 5 (“excellent”) following a number of criteria.
• Webharvy

16. WebHarvy ---
• It scrap the reviews but required cleaning
and preparation of data together.
• Put on local disk and google cloud

17. • Step 4: Data Exploration Analysis
Data Collection
Data
Preparation
Storage &
Structure on
Hadoop (HDFS)
Data Exploration
Sentiment
Analysis
Model Analysis
with Hadoop

18. Explore the most Important terms
It is topic modeling:
• Which term is more frequently
coming in review
• Well, we finalize following
words/terms
• Room, good, downtown, stay,
service, clean, room, pool, and
more
• Remember we did stemming,
punctuation, white space, and
many ore preprocessing step
before that
Room, location, value,
service

19. • Step 5: sentiment analysis
Data Collection
Data
Preparation
Storage &
Structure on
Hadoop (HDFS)
Data Exploration
Sentiment
Analysis
Model Analysis
with Hadoop

20. IS THIS ENOGH ? Answer is NO
• Take a list of positive and negative words
Positive
Good
Great
Fantastic
Excellent
Friendly
Awesome
Enjoyed
Negative
Bad
Worse
Rubbish
Sucked
Awful
Terrible
Bogus
I had a fantastic time on
holiday at your resort. The
service was excellent and
friendly. My family all really
enjoyed themselves.
The pool was closed, which
kind of sucked though.
4 1- = 3
Overall sentiment:
Positive

21. Sentiment Analysis with Neural Network
indeed it is good choice rather dictionary based
appraoch!

22. Dashboard – Sentiment Analysis of Dubai vs UK
hotel
• It is sentiment analysis
• Which give score of positive or
negative
• We evaluate the score of aspects
• Location , service, value, room
• We conclude that UK luxury
customers are more focusing on
location and service on the other
hand Dubai people focus on value
and room. Which Is vital fact for
GULF to re-consider.

23. Analyze aspect terms accuracy 95.81%
• It is K-Mean analysis
• Created clusters or groups for
aspects Location , service, value
• We concluded that our top terms
are better candidate for sentiment
analysis otherwise go again and
Find out other terms

24. Hadoop processing ML Model (Big Data)
• Configure Hadoop 2.8.3 version
• After starting Hadoop services HDFS
• We analyze k-mean in MAP-REDUCE to
process efficiently.

25. Other ML Model and IOT Integration
• Plan to integrate with IOT.
• Next will explore lights , sound and lock,
music player services of room because
people in GULF prefer room ambiance as
we analyzed.
• IOT devices in summer with dashboard
reflect the usefulness and effectiveness of
big data in tourism with more than 50
recommendation in our final report.
•

26. Plan
Activities
Months ( Academic year 2017-2018)
From September to
December
From January to April
From May
to June
Sept
201
7
Oct
201
7
Nov
201
7
Dec
201
7
Jan
201
8
Feb
2018
March
2018
April
201
8
May
201
8
June
201
8
Literature review
Data Collection & Scraping  
Data Preparation    
Data Insight    
Data Exploration 
Data Model    
Software Building   
Reports    
• We left 2 months to explore more
• 50 plus Recommendation
• Visualizing reports
• Finally more data on cloud to
• Convince ministry of tourism about
effectiveness of our project in the domain
of IOT + BIG.
• Google cloud will show the future plan
• And large scale storage benefits for
Ministry Hotels data around the world.

27. Thank you! Question start what I will do.. Not what you
did.

28. Works Cited
• https://data.gov.uk/dataset/road-accidents-safety-data
• https://www.thebalance.com/what-is-crowdsourcing-marketing-and-how-is-it-
used-2295467
• http://www.shu.edu/technology/
• http://archive.ics.uci.edu/ml/datasets.html?sort=nameUp&view=list
• http://www.dw.com/en/big-data-reveals-shakespeare-co-authored-17-of-his-
plays/a-36145979