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COVID-19 is an infectious disease that is introduced by a new coronavirus. The COVID-19 virus symptoms can include coughing, fatigue, fever for those with mild cases. For more severe cases, it can lead to shortness of breath, chest pain, and eventually death. Due to its infectious nature, people started taking health precautions that were advised by the World Health Organization such as social distancing, washing hands, and sanitizing surfaces. Due to this pandemic, the aim of this project is to automate mundane tasks with the help of a service robot to reduce physical contact as well as reduce the workload on healthcare workers. Tasks such as delivering food, medication, water, and other necessities to patients with infectious diseases. In addition, this project specifically reduces physical contact between patients and the attending nurse. A service robot is a robot that is built to perform a repetitive or dangerous task in order to assist humans. A service robot executes repetitive tasks more efficiently compared to a person who is prone to lose focus and make mistakes during work hours. The service robot performs tasks that are requested by the patients and accepted by the nurse through the mobile application. The application shows both the nurse and the patients the position of the robot and the task it is performing. The project’s design was based on a small robot car that receives a path from the server upon a request using a mobile app. On top of that, the project includes a functional mobile application, a RESTful API, a no-SQL database, and a python microservice that is responsible for path planning. The path planning algorithm used is the A* algorithm for finding the shortest path to the destination. The service robot avoids obstacles by first stopping after detecting the obstacle, label the coordinates of that location as obstacle, rotates 180 degrees, moves to the previous location, and then requests the path again. The constant communication between the robot and the server allows the server to track the robot’s movement.

Pressure ulcers, also known as bedsores, are severe complications in patients who have a low level of sensation with limited mobility such as people with quadriplegia, broken limbs, coma, high obesity, and elderly. Bedsores are critical; they can reach bones and muscles which make them hard to recover. The aim of this paper is to provide a solution that reduces the possibility of developing bedsores for long-term patients. Internet of Things (IoT) has a crucial role in healthcare monitoring applications due to its ability to provide a continuous monitoring system, which helps making efficient decisions for patients in real-time that reduce errors, wasted time, and costs. The proposed system is IoT based system, which monitors the patient's conditions depending on body temperature, skin humidity, and body immobility duration, which are the main causes of bedsores occurrence. The system also provides an action towards the patients' measured signs by releasing gentle air with suitable temperature through vents from the mattress of the patient's bed. Moreover, the system has a mobile application to maintain the ability to monitor the patients by the concerned parties remotely.

Mobile crowd-sensing (MCS) is a new sensing paradigm that takes advantage of the extensive use of mobile phones that collect data efficiently and enable several significant applications. MCS paves the way to explore new monitoring applications in different fields such as social networks, lifestyle, healthcare, green applications, and intelligent transportation systems. Hence, MCS applications make use of sensing and wireless communication capabilities provided by billions of smart mobile devices, e.g., Android and iOS-based mobile devices. The aim of this paper is to identify and explore the new paradigm of MCS that is using smartphone for capturing and sharing the sensed data between many nodes. We discuss the main components of the infrastructure required to support the proposed framework. The existing and potential applications leveraging MCS are laid out. Furthermore, this paper discusses the current challenges facing the collection methodologies of the participants’ data in task management. The recent issues in the MCS findings are reviewed as well as the opportunities and challenges in sensing methods are analyzed. Finally, open research issues and future challenges facing MCS are highlighted.

The current urban planning trend is to build smart cities that are advanced, safe and sustainable. To build these cities several technologies could be exploited including the Internet of Things (IoT) and edge computing. This motivated us to develop an IoT-based fire alarm system that uses edge computing. The developed system would be suitable in smart cities, as it mitigates issues faced by the existing fire alarm systems like installation overhead and lack of remote warning. Our system is an ad-hoc network of several sensing nodes and a single central node. Each of these sensing nodes consists of an ESP8266-nodeMCU connected to different types of sensors, such as smoke, temperature, humidity, flame, Methane and Carbon Monoxide (CO) sensors. These nodes are responsible for sensing the environment and detecting fire which means that they are smart end nodes and hence satisfying one of the characteristics of edge computing. The nodes transfer their readings to a centralized node that was implemented with a Raspberry Pi computer. Communication between the sensing node and the central node is through Message Queuing Telemetry Transport (MQTT) protocol which is carried via a bridge node. When a node detects fire, it signals the centralized node to alert the user and the fire department using the attached 4G module. An SMS is sent to them and the user is called. Users can inquire about the status of their home by sending an SMS. A prototype for the system performed the desired functionalities successfully with an average delay of less than 30 seconds and a node coverage of 1400m2.

Fire alarm systems are essential in alerting people before tire engulfs their homes. However, tire alarm systems, today, require a lot of wiring and labor to be installed. This discourages users from installing them in their homes. Therefore, we are proposing an IoT based wireless fire alarm system that is easy to install. The proposed system is an ad-hoc network that consists of several nodes distributed over the house. Each of these nodes consists of a microcontroller (ESP8266 nodeMCU) connected to smoke, temperature, humidity, flame, Methane and Carbon Monoxide (CO) sensors that continuously sense the surrounding environment to detect the presence of fire. The nodes create their own Wi-Fi network. These nodes communicate with a centralized node implemented with a Raspberry Pi microcontroller integrated with a 4G module. Once fire is detected by a node, it sends a signal to a centralized node that is triggered to send an SMS to the fire department and the user, call the user and alert the house by producing a local alarm. The user can also get information about the status of his home via sending an SMS to the system. The sensing nodes create a mesh network and they are linked to the central node via a bridge node. Communication between the bridge node and the sensing node is through Message Queuing Telemetry Transport (MQTT) protocol. A prototype was developed for the proposed system and it carried out the desired functionalities successfully with an average delay of less than 30 seconds. - 2019 IEEE. Scopus

This paper presents an optimization framework to maximize the lifetime of wireless sensor networks for structural health monitoring with and without energy harvesting. We develop a mathematical model and formulate the problem as a large-scale mixed integer non-linear programming problem. We also propose a solution based on the Branch-and-Bound algorithm augmented with reducing the search space. The proposed strategy builds up the optimal route from each source to the sink node by providing the best set of hops in each route and the optimal power allocation of each sensor node. To reduce the computational complexity, we propose heuristic routing algorithms. In this heuristic algorithm, the power levels are selected from the optimal predefined values, the problem is formulated by an integer non-linear programming, and the Branch-and-Bound reduced space algorithm is used to solve the problem. Moreover, we propose two sub-optimal algorithms to reduce the computation complexity. In the first algorithm, after selecting the optimal transmission power levels from a predefined value, a genetic algorithm is used to solve the integer non-linear problem. In the second sub-optimal algorithm, we solve the problem by decoupling the optimal power allocation scheme from the optimal route selection. Therefore, the problem is formulated by an integer non-linear programming, which is solved using the Branch-and-Bound space-reduced method with reduced binary variables (i.e., reduced complexity), and after the optimum route selection, the optimal power is allocated for each node. The numerical results reveal that the presented algorithm can prolong the network lifetime significantly compared with the existing schemes. Moreover, we mathematically formulate the adaptive energy harvesting period to increase the network lifetime with the possibility to approach infinity. Finally, the minimum harvesting period to have infinite lifetime is obtained.

Harvesting of vibration energy from the ambient environment, such as vibrations experienced by bridges due to vehicle movements, wind, earthquakes, has become an essential area of study by many scientists aiming to design new systems which can improve self-powered network sensors in wireless sensor networks (WSN), thus providing a more efficient system that does not require the human involvement.One of the essential components of WSN systems is the sensor node. It is used to continuously send/receive information to monitor a certain behavior targeted by the application; for example, to monitor bridge infrastructure's health. Sometimes, sensors are programmed and adjusted to send useful data for monitoring 24 hours a day, seven days a week. This configuration harms the sensors' batteries and shortens their lives, since sending/receiving data consumes power and leads to the reduction of the batteries' voltage levels. Due to this fact, energy harvesting is critical to maintaining long-term batteries that can recharge themselves from the available ambient harvested energy and eliminate the need for human involvement in replacing or recharging them in their specified locations in the network.Recent structural health monitoring systems (SHM), in civil infrastructure environments, have focused heavily on the use of wireless sensor networks (WSNs) due to their efficient use of wireless sensor nodes. Such nodes can be fixed onto any part of the infrastructure, such as bridges, to collect data remotely for monitoring and further processing. However, the drawback of using such sensor networks relies mainly on the finite life-time of their batteries. Due to this problem, the concept of harvesting energy from the ambient environment became more important. Ensuring efficient battery usage would have a great benefit in maximizing overall systems functionality time and ensures efficient use of natural energy resources like solar, wind and vibration energies.This work aims to study the feasibility of using a piezoelectric vibration energy harvester to extend overall battery life using a single, external, super-capacitor component which is serving as a storage unit for the harvested energy. The methodology followed in this work states the general direction of the flow of energy in a sensor node which can be summarized into the following:1 Piezoelectric Vibration Energy Harvester: This module was used to convert mechanical energy of the vibrations from the ambient environment to electrical energy.2 Energy Harvesting Circuit: This circuit is responsible for the power conditioning, enabling the circuit to output energy to the sensors under certain threshold criteria.3 Energy Storage: This the super-capacitor served to store harvested energy.4 Energy Management Scheme: The scheme proposed by this work under the energy requirements and constraints of the sensor nodes in order to conserve batteries voltage level to extend sensors' batteries lives.5 Wireless Sensors Nodes: Each sensor node type has specific energy requirements that must be recognized so that it can be adequately powered and turned on using the harvested energy.The main contribution of this work is a proposal of an energy management scheme which ensures that the harvested energy being provided to the harvester circuit must be greater than the energy output that is going to be consumed by the sensor. This proposed scheme has proved the feasibility of using impact vibrations for efficient energy harvesting and subsequently increase the battery life time needed to turn on the wireless sensor nodes.Furthermore, as a future direction of work, to increase the amount of harvested energy, hybrid power sources can be explored by combining more than one energy source from the ambient environment, such as solar and vibration energy.

We live in a new era where education is not anymore restricted to grouping individuals in a room and feeding them information. We also live in the same era where we deal with our handheld devices more than any other normal human interaction. Why then don't we implement a new “environment” to deliver education to our handheld devices that we hold and interact with? We need to free the process of education from physical presence to “virtual” presence through the power of the Internet, and this is the motivation driving us to solve our problem. We approach the new paradigm of the World Wide Web to have a web-based application for the instructor to access to be able to create and edit m-Learning objects and upload it to the assigned remote database, where the learner gets a notification for new objects to download to their handheld client application to learn and be assessed in. Previous technologies have been patented and applications have been done to solve the same problem, but we stand with the advantage of web-availability. The sole purpose of our work presented in this document is to enrich the process of education.

This research project addresses "Human Capacity Development" which is one of Qatar's Cross-cutting Research Grand Challenges. This grand challenge, which is a priority for Qatar, aims to develop sustainable talent for Qatar's knowledge economy in order to meet the needs for a high-quality workforce. As Qatar moves into the 21st century, it is important that Qatar develops its workforce to become more competitive and a model country for others to follow. At the same time, the quality of life of Qataris will be advanced. This presentation will describe a leading edge research project using emerging mobile training technologies to train workers in the oil and gas industry in Qatar. This project is funded by the Qatar National Research Fund. Subjects for this research project were employees at Qatar Petroleum. A total of 70 employees participated in this research project. The training was delivered on a variety of mobile devices which allowed employees to access the training materials from anywhere and at anytime. The research used a pre-post test design where a pre-test was administered before the employees took the training and a post-test was administered after the employees completed the training. The average percent score on the pre-test was 71 percent while the average score on the post-test was 79 percent indicating that employees' performance improved after completing the training using the flexible delivery method. In terms of the amount of time the employees spent on completing the training lesson, the time ranged from less than 30 minutes to more than three hours indicating the flexibility that mobile learning provided in training workers. In terms of where employees completed their training, 44 percent said that they completed some of the training at work and some at their home/residence; 22 percent completed the training at their home/residence; 19 percent completed the training either at work, home, or while travelling; and 15 percent completed the training at work. Again, these results show the flexibility that mobile learning provides in training. The results from this research project conducted at Qatar Petroleum show that the use of mobile technology for training workers improved performance and provides flexibility when and where workers completed their training. Delivering training using emerging mobile technology is important for the young generation of Qatari who are comfortable using mobile technology. Also, because of the flexibility of using mobile technology in training, workers can use the technology for just-in-time training so that they can apply when they learn right away which will facilitate high level learning. This research projects developed best practices for using mobile technology in training which will result in a paradigm shift in training to develop Qataris for the 21st century workforce. A well-trained Qatari workforce is important to achieve Qatar National Vision which aims at "transforming Qatar into an advanced country by 2030, capable of sustaining its own development and providing for a high standard of living for all of its people for generations to come"

This research paper is devoted for discussing a Vision-Based Collision Avoidance System that aims to provide the driver with a “third eye” to help him/her to detect obstacles and estimate distance between them and the host vehicles. It is based on a monocular approach of image processing that has one camera, which continuously captures images of the frontal view of the vehicle. Then the captured images are processed in order to detect obstacles, then estimate their distances from the host vehicle and, finally, take decisions to avoid them. The detection algorithm depends on detecting the shadow of the obstacles, as an invariant feature for all types of obstacles. Watershed segmentation technique is used to detect objects and triangulation technique is used to calculate the distance between the host vehicle and the detected obstacle. The proposed system can automatically control electric vehicles.

Many students in first year of computing majors find programming subject difficult to grasp. This paper describes an e-learning supportive system that is designed as learner-centered system to help novice computer programming students with object-oriented concepts. The system aims to improve students' satisfaction and motivation by using multiple instructional strategies. The paper presents the features of this system and discusses the empirical results of the effectiveness of using this system on students' satisfaction.

Multimedia documents compose different types and formats of media objects, such as video, audio, animations, still images, and text, in one scenario forming one big composite media object. The continuous evolution of new types and formats of media objects leads to the appearance of new players for each type and format. Accordingly, the multimedia documents players should handle the new types and formats as soon as they appear. This implies that the multimedia player should be designed to be easily extensible to handle new media objects. The extensibility can be achieved using object-oriented design supported by the design patterns. In this paper, we present a design pattern-based design and implementation of an extensible multimedia document player. We will present the design of the main components of the player, such as the individual media objects players, the time scheduler, and the clock. We will present as well how to represent the media object states, using object-oriented approach, and the inter-states transitions.