Best Postgraduate Student Award 2019

Milestone Achievement Unveiled: Dr. Ir. Fazilah Bt Mat Yatim Completes Intensive Research Pursuit, Garnering Well-Deserved Commendations

In a triumphant culmination of her academic journey, Dr. Ir. Fazilah Bt Mat Yatim, a dedicated and accomplished PhD student, has reached the pinnacle of her research endeavor, marking a significant milestone in the field of [Field of Study]. With profound admiration and hearty congratulations, her peers, mentors, and the academic community at large join together to acknowledge her remarkable feat.

The monumental “Hooding Ceremony,” meticulously planned to honor the profound achievement of Dr. Ir. Fazilah Bt Mat Yatim, is poised to transpire on the first day of November in the year 2019. This celebratory event is poised to grace the elegant surroundings of Dewan Kencanapuri, nestled within the prestigious enclave of Pulai Springs Resort, Johor Bahru, setting the stage for an evening filled with reflection, accolades, and collective pride.

Dr. Ir. Fazilah Bt Mat Yatim’s journey has been marked by relentless dedication, unyielding passion, and a pursuit of excellence that has set her apart. Her research voyage, spanning a substantial period, stands as a testament to her unwavering commitment to advancing knowledge and contributing to the scholarly discourse within her chosen field. As she embarks on the next chapter of her academic and professional journey, her success serves as an inspiration to aspiring scholars, affirming the boundless rewards of hard work, diligence, and unshakable determination.

The forthcoming “Hooding Ceremony” is anticipated to draw an esteemed gathering of academics, peers, family members, and friends, all eager to extend their heartfelt congratulations and honor the accomplishment of Dr. Ir. Fazilah Bt Mat Yatim. The ceremonious event promises to be a blend of tradition and innovation, punctuated by the resonant applause that accompanies the donning of the doctoral hood—a symbol of scholarly achievement and an emblem of the transformative impact that her research promises to impart.

As the sun sets on November 1st, 2019, and the vibrant atmosphere of Dewan Kencanapuri becomes awash with a sense of accomplishment and anticipation, Dr. Ir. Fazilah Bt Mat Yatim’s name shall be etched into the annals of academic excellence, a shining star that will undoubtedly continue to illuminate the academic landscape for generations to come.

Bengkel Laman Web

29 Oktober 2019. Bengkel Laman Web di Makmal Pengajaran 1, Bangunan N28A, Sekolah Perkomputeran, Fakulti Kejuruteraan, Universiti Teknologi Malaysia. Dikelolakan oleh Sdr. Mohd Sharul Hafiz bin Razak dari Unit Webmaster UTM.

Mobile Application Development

Mobile computing has changed the way we learn, interact with online services, and manage information. The popularity of handheld devices among people of all ages and cultures has increased the demand for highly interactive and user-friendly mobile apps. The multitude of sensors available on mobile devices such as GPS, ambient light sensing, and accelerometers have broadened the use of mobile apps in various application domains. Mobile apps vary widely, from weather forecasting and managing a patient’s health to providing online education, among many others.

Both students and lecturers of software engineering with a particular focus on mobile app development struggle to find a self-contained guide on how to follow the development life cycle of a mobile app project. In the great majority of these projects, the process generally follows a traditional software development life cycle—namely, setting up a set of requirements and then following an incremental development of the mobile app up to the achievement of acceptable functionality and design.

A mobile app is, however, very different from a desktop application. For instance, mobile apps are expected to run on multiple mobile operating systems, various screen sizes, and diverse technologies. Testing of mobile apps is therefore different from that of desktop applications. Additionally, mobile apps differ in their context of use and may need to take a number of factors into consideration including internet connection availability and speed, computational complexity, memory requirements, battery status, and accessibility features. These factors affect the software life cycle of a mobile app project and therefore more suitable architectures, design patterns, and testing approaches are needed. In practice, students as well as developers use their experience in desktop application development and customize the methodologies and tools to fit the particularities of a mobile app.

Source: Ghita Kouadri Mostefaoui Faisal Tariq (2019). Apps Engineering Design, Development, Security, and Testing. CRC Press.

GIS-Based Success Factors

Besides conducting a comprehensive needs assessment that helps adequately define the user needs and identify the available resources within the NSO and in the country, particularly the funding requirements, we need to consider critical factors to succeed in a full digital GIS-based census program. Chief among these factors are:

  1. ensuring senior management commitment to developing a long-term digital program;
  2. building the technical and human capacities required for sustaining the GIS-based systems and databases and setting up an independent unit for cartography and GIS activities within the NSO;
  3. using technical standards;
  4. forming a partnership to work together with the NMA and other groups that do things with geospatial information; and
  5. choosing the appropriate methodology of integration of the new geospatial technologies with the census mapping operations (compatibility).

These factors are revealed by survey-based study findings and lessons learned from country experiences during the last round of censuses in 2010.

See details in Australia Programme Review and the related background paper on Developing a Statistical Geospatial Framework in National Statistical Systems: Survey of Linking Geospatial Information to Statistics—Analysis of Questionnaire Responses (2013), available at https://unstats.un.org/unsd/statcom/44th-session/documents, and the UNSD report on the Results of a Survey on Census Methods Used by Countries in the 2010 Census Round, available at https://unstats.un.org/unsd/censuskb20/KnowledgebaseArticle10696.aspx.

Top five trends in GIS technology

According to Dangermond, the top five trends in GIS technology today are as follows:

  1. Location as a service
  2. Advanced analytics
  3. Big data analytics
  4. Real-time GIS
  5. Mobility

Dangermond continues: “The last leap in computing was the shift from the server to the cloud. Software as a service (SaaS) opened a world of opportunities for GIS, as shared map services like the World Imagery basemap are no longer separate from the unique services offered to users. GIS users can share data, collaborate, make mashup maps in the server, and then connect to the cloud.

The next leap in GIS technology and computing is connecting to the vast network of devices providing data in real time. This technology is a revolutionary change and brings great opportunity. The more accessible data is, the more important it will be to understand it. And maps are the visual language for understanding the context of data.”

Excerpt From: Amor Laaribi. “GIS and the 2020 Census.” iBooks.

Esri Geodatabase

“The Esri geodatabase is object-relational and illustrates the object-oriented concepts extension brought to relational-based databases. The subsequent examples will rely on the use of this geodatabase.”

Excerpt From: Amor Laaribi. “GIS and the 2020 Census.” iBooks.

Database Modeling

Using abstraction from concepts by humans to their implementation in the machine, database modeling relies generally on a three-tier model:

  1. A conceptual model involving the identification of the geographic features to be included in the database as entities/objects, the definition of their attributes, and how they relate to one another. An abstraction and objective representation of the real world independent from the DBMS software to be used.
  2. A logical model, a resulting outcome from the transformation of the conceptual model using the DBMS data model techniques (e.g., relational, object, or object-relational).
  3. A physical model, a resulting outcome from the transformation of the logical model, dealing with storage devices, file structure, and access methods that sort data records. A physical model deals with the storing and encoding of data—the lower-level data structure of the database.”

Excerpt From: Amor Laaribi. “GIS and the 2020 Census.” iBooks.

Geocoding

Geocoding (geographically enabling unit records) is defined as the process of finding associated geographic coordinates (expressed in latitude and longitude) from other geographic data for the statistical units, such as street addresses or postal codes. (Geocoding is a way to ensure that the data “knows” where it is.)
In other words, geocoding involves taking location information for these statistical units (such as address) and linking this information to a location coordinate (i.e., x,y,z coordinates) and/or a small geographic area. The geocodes (the location coordinates and geographic areas codes) obtained from this process can be stored directly on the statistical unit record or linked in some way to the record. There is a common misunderstanding between geocoding and georeferencing, so it is important to emphasize that while they are related, they are quite different. Georeferencing is often done, for example, with raster images. Georeferencing is the process of referencing data against a known geospatial coordinate system by matching to known points of reference in the coordinate system so that the data can be analyzed, viewed, and queried with other geographic data.

In the GIS industry, geocoding is synonymous with address matching, which is the process of assigning map coordinate locations to addresses in a database.30 A GIS is capable of doing this by comparing the elements of an address or a table of addresses with the address attributes of a reference dataset—the GIS data layer used as the geographic reference layer (e.g., a city’s street centerlines layer)—to find a match (i.e., to determine whether particular address falls within an address range associated with a feature in the reference).

But the concept of geocoding goes beyond address matching. It covers a continuum of spatial scales: from individual housing units to EA levels, up to higher administrative or national levels. The use of GPS, directly capturing precise data at the level of point locations (latitude and longitude coordinates), allows the coding of centroids, building corners, or building point-of-entry coordinates for a unit such as a block of land, building, or dwelling.

Excerpt From: Amor Laaribi. “GIS and the 2020 Census.” iBooks.

Open

“Many other considerations pertain to “open”: open data, open specifications, open APIs, open source, and, most importantly, open systems that are standards-compliant and interoperable for an open community.”

Excerpt From: Amor Laaribi. “GIS and the 2020 Census.” iBooks.

Finding the best locations and paths

“A very common type of spatial analysis, and probably the one you are most familiar with, is optimization and finding the best of something. You might be looking for the best route to travel, the best path to ride a bicycle, the best corridor to build a pipeline, or the best location to site a new store.

Using multiple input variables or a set of decision criteria for finding the best locations and paths can help you make more informed decisions using your spatial data.

Types
• Finding the best locations that satisfy a set of criteria
• Finding the best allocation of resources to geographic areas
• Finding the best route, path, or flow along a network
• Finding the best route, path, or corridor across open terrain
• Finding the best supply locations given known demand and a travel network”

Excerpt From: Amor Laaribi. “GIS and the 2020 Census.” iBooks.

Understanding Where

“If you don’t know where you are, you are lost. Understanding where is about putting the world in context. Where are you? What is around you? Very similar to when you were two years old, your journey of spatial analysis requires an understanding of how you fit into your geography.

Understanding where includes geocoding your data, putting it on a map, and symbolizing it in ways that can help you visualize and understand your data. Within the taxonomy of spatial analysis, the first category of understanding where contains three types of questions.

Types:
• Understanding where things are (location maps)
• Understanding where the variations and patterns in values are (comparative maps)
• Understanding where and when things change”

Excerpt From: Amor Laaribi. “GIS and the 2020 Census.” iBooks.

Geoblockchain

“A blockchain is a growing list of records, called blocks, which are linked using cryptography. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. It is a ledger that records transactions in a verifiable, permanent way.”

“Geography is critically important to capture in a blockchain record, which is why we are now calling this a geoblockchain.”

“Adding location to the blockchain would provide enhanced security and validation because the same transaction cannot happen in two places at the same time. Use cases for blockchain being explored today include land title, supply chain, and data exchanges. The amount of data that will become available with systems like these is worth consideration and needs research.”

Excerpt From: Amor Laaribi. “GIS and the 2020 Census.” iBooks.

Where My Location Data come from?

Basically, your Browser feature -Geolocation-, will try to determine your position using one of these several ways. These list, show the ordered devices about what Geolocation will give your location.

  1. GPS (Global Positioning System)
    This happen for smartphone / anything which has GPS inside. If you have smartphone with GPS capabilities and set to high accuracy mode, you’ll likely to obtain the location data from this. GPS calculate location information from GPS satelite signal. It has the highest accuracy. In most Android smartphone, the accuracy can be up to 10 metres.
  2. Mobile Network Location
    This happen if you use a wireless modem or phone without GPS chip built in it. Rather than GPS satellite’s signal, this one use signal from mobile provider. The accuracy may vary. 
  3. WiFi Positioning System
    If you are indoor, and using Wifi, this is the likely you’ll get. Some WiFi have location services capabilities, which able to obtain or save location data. If you’re concern with this stuff, try accessing this website from laptop with your Wifi network. If you can get exact location with very good accuracy, then your WiFi might have such feature. 
  4. IP Address Location
    This one will detects your location based on nearest Public IP Address on your devices, (can be your computer, or the router, or your ISP provider). Depend on the IP information available, but in many case, the public IP is often hidden behind Internet Service Provider NAT, resulting poor accuracy. This is the most often case for PC / laptop user which access internet from cable LAN, or WiFi without Geolocation capabilities. The accuracy is in level of city, region, or even country.

Source: https://mycurrentlocation.net

Development of Web-Based Application for Shapefile Coordinate System Conversion for Malaysia


By Elysonia Alim and Shahabuddin Amerudin

It is difficult to process GIS vector data when they are not aligned with one another. The need for different coordinate systems rose from the fact that some coordinate systems are better fitted to describe the geographical phenomenon occurring in a specific area. However, even commercial software had been proven to have questionable accuracy in coordinate system conversions. The purpose of this study is to develop a web application capable of converting the coordinate system of a GIS data format such as a shapefile for Peninsular Malaysia. The web application named Coordinate Conversion Application (CCA v1.1) was developed using Django 2.0 with Python 3.6 and is capable of five-coordinate transformations namely WGS84 to GDM2000 (forward and backward), WGS84 to MRSO (old) (forward only), MRSO (old) to Cassini (old) (forward and backward). Results obtained were compared with existing software such as GDTS v4.01 and ArcGIS 10.3, and analysis shows that CCA v1.1 has achieved satisfactory accuracy.

Published in Proceedings Asian Conference on Remote Sensing ACRS 2018 pg. 449

Development of Web-Based Application for Shapefile Coordinate System Conversion for Malaysia

Elysonia Alim and Shahabuddin Amerudin

Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
Email: elysoniaalim@gmail.com; shahabuddin@utm.my

KEYWORDS: coordinate system, conversion, shapefile

ABSTRACT: It is difficult to process GIS vector data when they are not aligned with one another. The need for different coordinate systems rose from the fact that some coordinate systems are better fitted to describe the geographical phenomenon occurring in a specific area. However, even commercial software had been proven to have questionable accuracy in coordinate system conversions. The purpose of this study is to develop a web application capable of converting the coordinate system of a GIS data format such as a shapefile for Peninsular Malaysia. The web application named Coordinate Conversion Application (CCA v1.1) was developed using Django 2.0 with Python 3.6 and is capable of five-coordinate transformations namely WGS84 to GDM2000 (forward and backward), WGS84 to MRSO (old) (forward only), MRSO (old) to Cassini (old) (forward and backward). Results obtained were compared with existing software such as GDTS v4.01 and ArcGIS 10.3, and analysis shows that CCA v1.1 has achieved satisfactory accuracy.

Topic: Web GIS Applications

Download Published Paper