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Nowadays, the Internet provides a strong technical support for the construction and development of smart home.Smart home sets the user's living environment as the central platform, and USES many technologies such as Internet of things, radio frequency identification, etc., to practice the unification, intelligent management and regulation of all indoor household appliances, which has obviously improved people's living quality and created convenient conditions for users to manage household appliances.Under the pressure of high technology, the current smart home products on the market are of various types, diverse functions, each has its own advantages, most of the products are mainly used to regulate the switch quantity, analog quantity control involved in the degree of insufficient, unable to achieve the indoor lighting degree of fast and accurate regulation.This paper mainly develops a remote control system based on Android mobile terminal, and explores the specific method for the system to control the brightness of smart home lamps, so as to further improve the level of intelligence of smart home and the satisfaction of residents.

Sensor data pre-processing is an essential phase of crowd sensing application. Existing studies do not effectively solve the problem, and there still exist various sensor data pre-processing optimisation problems at the acquisition end in crowd-sensing process. This study presents an improved sliding average method to achieve data compression and reduce the time complexity by using a dynamic window with improved processing time. Through adopting locally sorting and gradient change of the filter window, an improved extremum median filtering method is proposed to relieve the time-consuming problem when denoising high pixel images. A transmission strategy for optimisation is also proposed, in which only the demarcation points of each group of data and the data points with large differences when comparing with the demarcation points are recorded. This strategy reduces the storage pressure and the amount of data transmission of mobile terminal and improves the efficiency of data transmission. The experimental results show that their methods have higher speed and lower cost, and thus they can run better in crowd-sensing environment.

A new ultra-wideband (UWB) multiple-input/multiple-output (MIMO) antenna system is proposed for future smartphones. The structure of the design comprises four identical pairs of compact microstrip-fed slot antennas with polarization diversity function that are placed symmetrically at different edge corners of the smartphone mainboard. Each antenna pair consists of an open-ended circular-ring slot radiator fed by two independently semi-arc-shaped microstrip-feeding lines exhibiting the polarization diversity characteristic. Therefore, in total, the proposed smartphone antenna design contains four horizontally-polarized and four vertically-polarized elements. The characteristics of the single-element dual-polarized UWB antenna and the proposed UWB-MIMO smartphone antenna are examined while using both experimental and simulated results. An impedance bandwidth of 2.5–10.2 GHz with 121% fractional bandwidth (FBW) is achieved for each element. However, for S11 ≤ −6 dB, this value is more than 130% (2.2–11 GHz). The proposed UWB-MIMO smartphone antenna system offers good isolation, dual-polarized function, full radiation coverage, and sufficient efficiency. Besides, the calculated diversity performances of the design in terms of the envelope correlation coefficient (ECC) and total active reflection coefficient (TARC) are very low over the entire operating band.

In order to improve object detection ability of robot, this study introduces an object detection algorithm which is based on deep learning. Firstly, a neural network that contains Convolution Layer, Pooling Layer and Fullly Connection Layer is designed to recognize whether the target object in image. Secondly, the Faster-RCNN, as a typical object detection algorithm, is used to detect the position of target object in image. Finally, the algorithm is transplanted on Raspberry Pi for deployment and testing. Results show that this algorithm can work well on Raspberry PI, and the mAP (mean average precision) and FPS (frames per second) reach 97% and 3. Meanwhile, the position of target object is accurately marked in image. Therefore, this study implies that the object detection algorithm based on deep learning can be implemented on mobile terminal and is helpful to improve object detection ability of mobile terminal.

This paper presents a novel design of a Multiple Input Multiple Output (MIMO) antenna system for next generation sub 6 GHz 5G and beyond mobile terminals. The proposed system is composed of a main board and two side boards. To make the design cost-effective, FR4 is used as a substrate. The design is based on a unit monopole antenna etched at the side substrate. The single element is resonating at 3.5 GHz attaining a 10 dB bandwidth of 200 MHz and a 6 dB bandwidth of 400 MHz. The single element is then transformed into an MIMO array of 8-elements with an overall dimension of 150 mm × 75 mm × 7 mm, providing pattern diversity characteristics and isolation better than −12 dB for any two radiating elements. A number of studies such as effects of human hand on the system that includes single hand mode and dual mode scenarios and the effects of Liquid Crystal Display (LCD) over the principal performance parameters of the system are presented. The envelop correlation coefficient (ECC) is computed for all the scenarios and it is found that ECC is less than 0.1 for any case and maximum channel capacity is 38.5 bps/Hz within the band of interest. The main advantage of the proposed design over available designs in the literature is that almost all of the main substrate is empty providing wide space for different sensors, systems, and mobile technology components. A brief literature comparison of the proposed system is also presented. To validate the proposed model, a prototype is fabricated and results are presented. This design can be applied on higher frequencies to future micromachines for on chip communications using same theocratical approach as the space for higher frequencies in mmwave spectrum has been reserved. The simulated results are in an excellent agreement with the measured results. All the main performance parameters of the design are calculated and compared with the measured results wherever possible.

In this study, we propose a design of a multi-band slot antenna array applicable for fourth-generation (4G) and fifth-generation (5G) smartphones. The design is composed of double-element square-ring slot radiators fed by microstrip-line structures for easy integration with radio frequency (RF)/microwave circuitry. The slot radiators are located on the corners of the smartphone printed circuit board (PCB) with an overall dimension of 75 × 150 mm2. The proposed multiple-input multiple-output (MIMO) antenna is designed to meet the requirements of 4G and 5G mobile terminals with essential bandwidth for higher data rate applications. For −10 dB impedance bandwidth, each single-element of the proposed MIMO design can cover the frequency ranges of 2.5–2.7 GHz (long-term evolution (LTE) 2600), 3.45–3.8 GHz (LTE bands 42/43), and 5.00–5.45 GHz (LTE band 46). However, for −6 dB impedance bandwidth, the radiation elements cover the frequency ranges of 2.45–2.82 GHz, 3.35–4.00 GHz, and 4.93–5.73 GHz. By employing the microstrip feed lines at the four different sides of smartphone PCB, the isolation of the radiators has been enhanced and shows better than 17 dB isolation levels over all operational bands. The MIMO antenna is implemented on an FR-4 dielectric and provides good properties including S-parameters, efficiency, and radiation pattern coverage. The performance of the antenna is validated by measurements of the prototype. The simulation results for user-hand/user-head impacts and specific absorption rate (SAR) levels of the antenna are discussed, and good results are achieved. In addition, the antenna elements have the potential to be used as 8-element/dual-polarized resonators.

A novel and compact wideband multiple input multiple output (MIMO) antenna for mobile terminals is presented. The proposed antenna operates over a wide frequency range of 1.79–3.77 GHz suitable for long-term evolution (LTE), worldwide interoperability for microwave access (WiMAX) and wireless local area network (WLAN) handheld devices. The MIMO antenna structure consists of two identical radiators with a small size of 10 × 17.7 mm2 and a parasitic element with a T-shape. The radiators, which comprise four branches with a meandered strip feed, are symmetrically located with respect to the T-shaped parasitic element. The parasitic element is a novel design appended at the ground plane. By using this parasitic element, a better isolation performance has been achieved between the two radiators. The overall performance of the antenna in terms of s-parameters, radiation pattern, gain and envelope correlation coefficient is investigated and verified through measurements. The results obtained show that the proposed antenna has attractive physical properties due to being small, compact and embeddable in mobile handsets, and has good characteristics of wideband, isolation, gain and radiation pattern.

Next-generation wireless networks (NGWN) consist of the integration of various technologies, such as Mobile ad-hoc networks (MANET), Wi-Fi, WiMAX, and LTE which are connected to the internet. Switching off the nodes among networks with same or different technology is handled by mobile IP. The determination of hand-off is not solely reliant on received signal strength, as relying solely on this metric could result in unnecessary hand-offs. Various factors, such as power consumption in communication, delay, traffic load, and network bandwidth, also play crucial roles in ensuring successful transmission. This paper introduces a seamless hand-off technique based on Markov processes (S-MSH), which takes into account different network properties that impact the Quality of Experience (QoE) for mobile terminals (MT) during communication. The proposed approach focuses on creating a Markov Decision Process (MDP) model for the system, considering user traffic requirements. The Q-learning algorithm is applied to the model to predict whether a hand-off is beneficial. An integrated similarity index-based approach, termed S-MSH, has been introduced to expedite the convergence rate of MSH. Simulation and numerical results demonstrate that the proposed approach surpasses the performance of the Network Priority Multicriteria Vertical Handover Decision Algorithm (NPMH) and the Simple Additive Weighing Algorithm (SAW) in terms of total reward and the number of handoffs.

To solve the demand for road damage object detection under the resource-constrained conditions of mobile terminal devices, in this paper, we propose the YOLO-LWNet, an efficient lightweight road damage detection algorithm for mobile terminal devices. First, a novel lightweight module, the LWC, is designed and the attention mechanism and activation function are optimized. Then, a lightweight backbone network and an efficient feature fusion network are further proposed with the LWC as the basic building units. Finally, the backbone and feature fusion network in the YOLOv5 is replaced. In this paper, two versions of the YOLO-LWNet, small and tiny, are introduced. The YOLO-LWNet was compared with the YOLOv6 and the YOLOv5 on the RDD-2020 public dataset in various performance aspects. The experimental results show that the YOLO-LWNet outperforms state-of-the-art real-time detectors in terms of balancing detection accuracy, model scale, and computational complexity in the road damage object detection task. It can better achieve the lightweight and accuracy requirements for object detection for mobile terminal devices.