In the current era of technological advancement, Internet of Things (IoT) has become a technology that is frequently adopted in all industries. The IoT concept that allows multiple devices to interact with each other over an increasingly popular internet connection is used in everyday applications automatically as well as for monitoring and security purposes. Ornamental plants, vegetables and herbs that can be grown in or around the house that are often left for working residents can apply this IoT system. Residents not only get the view of green and fresh air, but they can also produce fast and fresh food from their own pots with the help of automatic monitoring and planting systems. An efficient irrigation process can be achieved with an IoT approach as it ensures that the plant or plants get the right amount of water to grow well. Therefore, an automated planting system based on the Internet of Things is proposed to solve problems related to the need to irrigate plants when necessary and monitor plant conditions remotely.

During the Fourth Industrial Revolution (IR 4.0) era, personal electronic devices such as smartphones, laptops, and computers have become common in an individual’s daily activities. These devices have been used to communicate with others through various social media platforms such as Facebook, Youtube, Wechat, Whatsapp, and others. When the globe is facing the pandemic Covid-19, the importance of the devices had become more significant, along with the increased usage of digital wallets to enable contactless payments. Without literacy skills, an individual is far more likely to live in poverty and may be isolated in a world increasingly dependent on electronic devices. Although the Government of Malaysia has been putting a lot of effort to ensure that indigenous people’s education system is at a reasonable level, there are no significant and robust changes. The illiterate indigenous adults might still be left behind due to their inability to read. Thus, the main objective of this study is to develop a specialized user-friendly mobile educational application prototype to reduce the illiteracy rate among indigenous adults in Malaysia Personal Extreme Programming (PXP), which is the derivative of the Extreme Programming (XP) of the agile method was adopted to develop the mobile. The application is being developed with the intention to reduce the illiteracy rate among indigenous adults in Malaysia. The overall findings indicate that respondents are satisfied with Belajar SenangJer as it facilitates the learning of Malay language through flashcards and videos. In the future, the user interface of Belajar SenangJer could be improved by providing a voice guidance function and matching games. The application could be expanded to learn more languages, such as English and Mandarin.

The pandemic of Covid-19 transforms our daily life by bringing new norms which makes Internet as an essential component in our everyday routine. With regard to this, both parents and kids are also fully depended on the Internet for their online classes, assessments and for work purposes. Unfortunately, the kids lose track of time while accessing Internet, which seem to be more entertaining. Currently, majority parents were found struggling to monitor their kid’s Internet usage. Thus, this project proposes a mobile application for Internet usage monitoring aiming to assist parents who are concern on their kid’s Internet usage. This project involved Rapid Application Development (RAD) methodology for developing the mobile application. The outcomes of this project are beneficial for parents not only for monitoring purposes but also as a training platform for their kids during this transition period.

Prihatin Kedah is a Kedah based non-governmental organization (NGO) that rely extensively on volunteers to achieve the NGO’s goals. The purpose of this project is to develop a Volunteer Activities Tracking System (VATS) that are capable of tracking the volunteers’ activities, and can also provide an intermediary between NGO’s administrator and volunteers. All the volunteer activities are currently handled manually through the phone via WhatsApp. Volunteers have difficulties to keep track and view the schedules of events, activities, and locations. In addition, volunteers also face difficulties to communicate with the NGO’s admin to get updates of events and activities. The second problem is that it takes a lot of energy and required a lot of time to produce and generate report since they have to do it manually. They need to retrieve back and keep track of all the documents to find the information to produce a report which often lead to other problems such as duplication in data entry, data not accurate and others. The objective of the system is to serve as a platform to manage volunteer activities, to provide efficient way to track volunteer activities and to manage the process of volunteer activities easier for both volunteer and admin. Waterfall model is used in system development life cycle (SDLC) in this project which include phases of planning, analysis, design, testing, deployment and maintenance. With the system, availability of volunteers is matched with events, activities and location. Thus, allowing easy coordination of volunteers and admin also able to generate the report more accurately. The system effectively match the volunteers’ preferences with the NGO’s needs. Making admin task easier as the system provide a single platform to manage activities and produce report. Hence, this project provide a positive social impacts of the use of digital solution for community well-being.

Inadequate global recycling rates led the world to face a worsening waste management crisis. Humans keep producing numerous tons of waste every year while the landfills of the waste remain piled up and poison the world's health sustainability. Zero-Smart Recycle Bin is designed to promote recycling movement to achieve zero net carbon emission goals. The target of the system is notably for the environmentally conscious or recycling activist, as well as for other groups in society. This paper focuses on designing the system and discussing the proposed system. The system is designed to identify and segregate the waste into different categories such as paper, metal can, and plastic bottles. The device is designed to be operated automatically using Raspberry Pi3 due to The efficiency of the processor and the compatibility with the network . The Raspberry Pi3 is integrated with object visual detection by using YOLOv5 and inductive-capacitive sensors to identify the material of the waste. The system also involves an integrated web application as the user platform. The research has achieved in proposing the design of the system, however the realization of the system design into a real product yet is still beyond of this research. Further study is aviseably required to verify and test the proposed framework and algorithm to get more desired result in the future.

Face detection can identify and verify faces from images, videos, and other forms of face graphics. It tracks facial features, contours, and textures to analyze individuals’ unique biometrics and demographic details. Humans can express thousands of facial expressions, all of which vary in intensity, complexity, and meaning. Facial emotion recognition is a type of facial recognition system, and it is a technology that can detect human emotions through facial expressions. In the past few decades, real-time facial emotion recognition systems have been an active area of research. Due to the Covid-19 pandemic, most learning methods have changed from physical learning to online learning. Therefore, it is difficult for teachers to understand students' emotions in the teaching process, and some emotions constitute obstacles to students' classroom participation and test scores. Nowadays, as students, we also know that it is difficult for lecturers to capture the emotions of students through the online learning mode and change the learning mode according to the emotions of the students. As a result, most of the time students feel bored and cannot concentrate in class because they are not interested in the lecturer's learning mode. Therefore, the learning materials prepared by the lecturer will become invalid due to the inattention of students in class. In this project, we will use a facial landmark to detect real-time facial expressions via a webcam. The purpose of the project is to establish a facial emotion recognition system to recognize the emotions of students in class and view the report of the emotions of the students. The result of this project is to allow lecturers and students to better understand their emotions during class. By doing so, we can recognize emotions and classify learners’ participation and interest in topics that are mapped as feedback to the lecturer to improve the learner’s experience. In addition, after students use the system, there will be emotional results. For example, students can learn about their emotional changes during class hours.

Every year there will be thousands of students enrolling into universities. Before the starting of every semester, the head of department in all schools have a very important job which is deciding the numbers of classes/slots to be opened for every course and submit them to the Academic Affairs (HEA) office. The number of classes/slots for each course is determined based on the number of students enrolled for the course. Knowing the accurate number of classes/slots to be opened could help in allocating suitable lecture halls for each class/slot. This would then ensure the lecture halls are used to the fullest and the students would have a comfortable learning environment. The traditional method of counting the number of classes/slots manually course by course is rather troublesome and time consuming. Therefore, a web-based School of Computing (SOC) Course Slots Distribution System is developed to help solve the problem. The system aims to distribute the classes/slots for each course in BSc in Information Technology and BSc in Computer Science according to the number of students enrolled for the course. The system is developed using HTML, PHP and CSS. The system was then tested by the representatives of SOC management and evaluated based on user acceptance using an online survey platform – Google Form. The result of the evaluation suggested that the SOC Course Slots Distribution System is usable to assist the head of department of every school in Universiti Utara Malaysia (UUM) to calculate the number of classes/slots to be opened for each course efficiently. The respondents also suggested for the system to have lab allocation as well for further improvement. With the help of this system, the workload of head of departments will greatly decrease.