We present an Arduino-based automation system to control the streetlights based on solar rays and object’s detection. We aim to design various systems to achieve the desired operations, which no longer require time-consuming manual switching of the streetlights. The proposed work is accomplished by using an Arduino microcontroller, a light dependent resistor (LDR) and infrared-sensors while, two main contributions are presented in this work. Firstly, we show that the streetlights can be controlled based on the night and object’s detection. In which the streetlights automatically turn to DIM state at night-time and turn to HIGH state on object’s detection, while during day-time the streetlights will remain OFF. Secondly, the proposed automated system is further extended to skip the DIM condition at night time, and streetlights turn ON based on the objects’ detection only. In addition, an automatic door system is introduced to improve the safety measurements, and most importantly, a counter is set that will count the number of objects passed through the road. The proposed systems are designed at lab-scale prototype to experimentally validate the efficiency, reliability, and low-cost of the systems. We remark that the proposed systems can be easily tested and implemented under real conditions at large-scale in the near future, that will be useful in the future applications for automation systems and smart homes.

Sprouting populace mass within the urban areas furnishes critical challenges of providing uninterruptible community services to fulfill the primitive needs of inhabitants in smart cities. Smart cities facilitate and uplift the living standards of inhabitants through various smart systems or infrastructures, and smart grid is one of them. Secure transmission is a key requirement in the advanced metering infrastructure (AMI) of most smart grids, and key establishment cryptographic protocols can be used to achieve such a requirement. Designing efficient and secure key establishment protocols for AMI remains challenging.For example, in this paper, we reveal several weaknesses in the identity-based key establishment protocol of Mohammadali et al (published in IEEE Trans Smart Grid, 2017), which is based on elliptic curves. We then improve their protocol and prove its security in the random oracle model. We also demonstrate that the improved protocol achieves both anonymity and untraceability, before presenting a comparative summary of the security and computational overheads of the proposed protocol and several other existing protocols. KEYWORDSadvanced metering infrastructure, anonymity, identity-based key establishment, key establishment, smart grid Int J Commun Syst. 2019;32:e4137.wileyonlinelibrary.com/journal/dac

Improved Spectral Efficiency (SE) is a prominent feature of Massive Multiple-Input and Multiple-Output systems. These systems are prepared with antenna clusters at receiver (Rx) and transmitter (Tx). In this paper, we examined a massive MIMO system to increase SE in each cell that ultimately improves the area throughput of the system. We are aiming to find appropriate values of average cell-density (D), available bandwidth (B), and SE to maximize area throughput because it is the function of these parameters. Likewise, a SE augmentation model was developed to attain an increased transmit power and antenna array gain. The proposed model also considers the inter-user interference from neighboring cells along with incident angles of desired and interfering users. Moreover, simulation results validate the proposed model that is implementable in real-time scenarios by realizing maximum SE of 12.79 bits/s/Hz in Line of Sight (LoS) and 12.69 bits/s/Hz in Non-Line of Sight (NLoS) scenarios, respectively. The proposed results also substantiate the SE augmentation because it is a linear function of transmit power and array gain while using the Uniform Linear Array (ULA) configuration. The findings of this work ensure the efficient transmission of information in future networks.

A specially designed tunable hyperbolic metamaterial (HMM) based on plasmon induced transparency (PIT) of fractal in the near-infrared (NIR) regime was proposed. The HMM-layer constitutes the top metasurface, which is comprised of fractal-like nanospheres of silver (Ag) metal. A bilayer of graphene is sandwiched between the top HMM and bottom silicon (Si) substrate. The permittivity of graphene bilayer was deduced corresponding to different chemical potentials (of graphene). PIT of the proposed structure was obtained in the 3000-4000 nm wavelength band by employing the finite difference time domain simulation under the excitation of a fundamental transverse magnetic (TM) mode. The effects of incidence angle and graphene chemical potential on the transmission characteristics were investigated. Furthermore, the PIT windows could be tuned by altering the radii of Ag nanospheres in the HMM layer and chemical potential of bilayer graphene. Such systems would be useful in varieties of applications, e.g., switching, energy harvesting, sensing in environmental, and/or medical diagnostics, particularly in detecting the existing impurities in human blood and urine.

Photovoltaic (PV) energy is highly promising because of its renewable, green, and environment-friendly nature. In this article, the design and analysis of an isolated PV system using a push-pull converter with a fuzzy logic-based maximum power point tracking (MPPT) algorithm is presented. Furthermore, DC-DC converters, along with intelligent controllers fed with MPPT algorithms, are used to ensure the maximum extraction of incident energy. The proposed methodology utilizes fuzzy logic MPPT techniques based on an isolated push-pull boost converter to optimize the power output of PV modules, as well as to achieve isolation and high DC gain for DC/AC inversion. This work also presents a single-phase inverter with fuzzy logic close loop control analysis with LCL filter design. A Canadian solar panel of 250 W is assumed in this research work, which has an open circuit voltage 59.9 V, short circuit current 5.49 A at 25 • C temperature, and 1000 W/m 2 irradiance. The voltages are tracked, through the MPPT algorithm. These voltages represent a boost to 340 V DC through push-pull boost converter and are inverted up to 220 V AC through fuzzy logic voltage source inverter. In addition, a unipolar switching technique is used to remove the total harmonic distortion under linear load. The proposed methodology is simulated in MATLAB/Simulink. The simulation results verify that the proposed methodology can efficiently track the MPPT. Finally, the hardware prototype of the proposed system has been experimentally validated. K E Y W O R D S fuzzy logic control, maximum power point tracking, pulse width modulation, total harmonic distortion 1 INTRODUCTION Energy is the need of the modern world and there is a need to explore new means of energy, which are cheap and environment-friendly. The energy demand is increasing every year and already existing resources including thermal, hydro, nuclear, and gas are unable to meet the demand. There is a need for some alternate sources of energy that can meet This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Massive multiple-input multiple-output or massive MIMO system has great potential for 5th generation (5G) wireless communication systems as it is capable of providing game-changing enhancements in area throughput and energy efficiency (EE). This work proposes a realistic and practically implementable EE model for massive MIMO systems while a general and canonical system model is used for single-cell scenario. Linear processing schemes are used for detection and precoding, i.e., minimum mean squared error (MMSE), zero-forcing (ZF), and maximum ratio transmission (MRT/MRC). Moreover, a power dissipation model is proposed that considers overall power consumption in uplink and downlink communications. The proposed model includes the total power consumed by power amplifier and circuit components at the base station (BS) and single antenna user equipment (UE). An optimal number of BS antennas to serve total UEs and the overall transmitted power are also computed. The simulation results confirm considerable improvements in the gain of area throughput and EE, and it also shows that the optimum area throughput and EE can be realized wherein a larger number of antenna arrays at BS are installed for serving a greater number of UEs.

Objectives/ Methods: The conventional farming approaches have been found unable to deliver an appropriate quantity of fertilizer. Similarly, no explicit measure can be established to regulate the climate parameters. In this study, we have developed a prototype comprising a sensor network (SN) based node, Raspberry Pi based embedded system (ES) that is active to monitor the climatic parameters with air temperature, air humidity, soil moisture, air carbon dioxide, and light intensity within a greenhouse environment. Raspberry Pi based ES is integrated with internet-of-things (IoT) analytics, termed as ThingSpeak, and sensor nodes are physically placed in a greenhouse environment to record climate parameter data being forwarded to the gateway. The gateway nodes direct this data to the agriculture professional(s) through a web browser over the internet. Findings: Based on the received data, the ES triggers the intelligent decision-making by implementing appropriate arrangements to regulate climate parameters. For example, the greenhouse climate is controlled through switching``ON'' certain devices i.e., lights, water sprinklers/exhaust fan, and fan. We deliberate that the proposed scheme can be implementable at a bigger scale without any difficulty and it will be much advantageous for an increase in sustainability, productivity, and profitability of a farming system. Novelty: Up to the authors' best knowledge, it is the first wireless deployment of ThingSpeak analytics for a smart greenhouse environment by using the Raspberry Pi. The main advantages of this intelligent crop monitoring system include uninterrupted mobile monitoring of the greenhouse, improved crop yield and productivity, negligible human interface/dependency.

The increasing ratio of diabetes is found risky across the planet. Therefore, the diagnosis is important in population with extreme risk of diabetes. In this study, a decision-making classifier (J48) is applied over a data-mining platform (Weka) to measure accuracy and linear regression on classification results to forecast cost/benefit ratio in diabetes mellitus patients along with prevalence. In total 108 invasive and non-invasive medical features are considered from 251 patients for assessment, and the real-time data are gathered from Pakistan over a time span of June 2017 to April 2018. The results indicate that J48 classifiers achieved the best accuracy of (99.28%), whereas, error rate (0.08%), Kappa stats, PRC, and MCC are (0.98%), precision, recall, and F-matrix are (0.99%). In addition, true positive rate is (0.99%) and false positive is (0.08%). The regression forecast decision indicates blood pressure and glucose level are key features for diabetes. The cost/benefit matrix indicates two predictions for positive test with accuracy (66.68%) and (30.60%), and key attributes with total Gain (118.13%). The study confirmed the proposed prediction is practical for screening of diabetes mellitus patients at the initial stage without invasive medical tests and found effectual in the early diagnosis of diabetes.