With the surge of ubiquitous demand for high-complexity and quality mobile Internet-of-things (IoT) services, new cooperative relaying paradigms have emerged. Motivated by the long and unpredictable end-to-end communication in relay-aided IoT networks, there is a need to introduce novel modulation schemes for very low bit error rate (BER) communications. In this paper, a practical modulation mapping scheme has been proposed to reduce decoding errors. Specifically, a hybrid automatic repeat request (HARQ) system has been used with an intermediate relay to transfer a message from a source to a destination. The design of modulation mapping has been optimized by first formulating the objective as the quadratic assignment problem. Later, the solution to the mapping problem is provided using an iterative search method. To validate the proposed solution, extensive simulations have been performed in MATLAB. The results show that the proposed solution outperforms the conventional relay retransmission and the heuristic design approaches.

Irrigation operations in agriculture are one of the largest water consumers in the world, and it has been increasing due to rising population and consequent increased demand for food. The development of advanced irrigation technologies based on modern techniques is of utmost necessity to ensure efficient use of water. Smart irrigation based on computer vision could help in achieving optimum water-utilization in agriculture using a highly available digital technology. This paper presents a non-contact vision system based on a standard video camera to predict the irrigation requirements for loam soils using a feed-forward back propagation neural network. The study relies on analyzing the differences in soil color captured by a video camera at different distances, times and illumination levels obtained from loam soil over four weeks of data acquisition. The proposed system used this color information as input to an artificial neural network (ANN) system to make a decision as to whether to irrigate the soil or not. The proposed system was very accurate, achieving a mean square error (MSE) of 1.616 × 10 −6 (training), 1.004 × 10 −5 (testing) and 1.809 × 10 −5 (validation). The proposed system is simple, robust and affordable making it promising technology to support precision agriculture.

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The unassisted visual system cannot note minute temporal variations in video and image sequences. In many applications, these differences and small signals are highly informative. A new technique used to expose video variations by measuring and amplifying video variations over time in a fixed position (pixel) was used to Eulerian video magnification (EVM). The objective of the study is to investigate and evaluate different processes for the creation and testing of EVM techniques and video quality parameters for each one of those methods. This research employed four new methods; EVM, Riesz pyramid for fast phase-based video magnification (FPBM), phase-based video magnification (PBM), and Enhanced Eulerian video magnification (E2VM). The experimental findings compared with their output for certain enlargement methods; time and quality parameters of image. A new magnification method is required based on the study of the exiting methods, which takes account of noise elimination, video quality and time reduction.

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Wireless sensor networks (WSNs) and their applications have received significantly interested in the last few years. In WSN, knowing an accurate path-loss model as well as packet delivery should be taken into account for the successful distribution of several nodes in the network. This paper presents a path-loss modeling and performance evaluation of the ZigBee wireless standard. Received signal strength indicator (RSSI) measurements were achieved in outdoor and indoor environments to derive the path-loss based on Log-Normal Shadowing Model (LNSM). The path-loss parameters such as standard deviation and path loss exponents were estimated over point-to-point ZigBee WSN. In addition, the variances of received RSSI values and standard deviation for these values have been investigated. Furthermore, the data packets received is measured practically. Results revealed that the LNSM can be estimated to reflect the channel losses in both outdoor and indoor environments for medical application. The data delivery was achieved successfully of 100% in outdoor which better than indoor due to multipath propagation and shadowing. Moreover, the data packets delivery of the current work outperformed previous work.

The application of 3D scanner technology among industrial practitioner in Indonesia and Malaysia is still at the beginning stage. Compared to others, this technology has already been adapted mostly by growing country such as China, Korea, US, Germany and Italy. This technology can be seen implemented in manufacturing, aerospace, medical and dentistry industries. The concept of 3D scanner technology is mainly to improve the reverse engineering process. Due to the high cost of 3D scanner machine available in the market, therefore a reasonable cost-effective 3D scanner is needed to be developed especially for education purposes. The objective of this project is to develop low-cost 3D scanning setup to create a mesh of a small-scale object with the help of open-sources software for 3D scanning and 3D mesh processing. Triangulation technique was used for the scanning process to capture the object surface. Screened Poisson Surface Reconstruction techniques was applied to improve the uncomplete and uneven surface mesh. In order to test the setup, 3D scanning was conducted on 4 different objects with different colours and surface finish. The scanning results show that the proposed method produced a good 3D mesh with less noise and less uncomplete surface.

Irrigation consumes 70% of the water quantity used worldwide. In a context of rising food demand and declining in water resources, the development of advanced irrigation technologies based on modern techniques in agriculture is a significant demand to keep this resource safe. To achieve this target, the management of water resources in agriculture needs to be specified and controlled. This study aims to propose an automatic, non-contact and cost-effective soil irrigation system based on analysing the changes in loam soil colour captured by a digital camera at different illumination levels. A graphic user interface (GUI) attached to the Arduino Uno microcontroller was used to drive the water pump and determine whether the loam soil requires irrigation or not. The experimental results illustrate the effectiveness of the proposed irrigation system to determine soil state and provide an accurate decision for soil irrigating, thus making this system a promising approach in future irrigation technologies.