Optimization of n-MOS 6T Nanowire SRAM Bit Cell Based on Nanowires Ratio of SiNWTs

In nowadays technology, the primary memory structure widely used in many digital circuit applications is a six transistor (6T) Static Random Access Memory (SRAM) bit cell. The main reason for minimizing memory bit cell to nanodimensions is to provide the SRAM integrated circuits (ICs) with the possible largest memory size per one chip, and the main unit in 6T SRAM bit cell is the MOSFET. One of the new MOSFET structures that overcome conventional MOSFET structure problems under minimization towards nanodimension is the silicon nanowire transistor (SiNWT). This study is the first to explore and optimize the nanowire ratio of driver to load (KD/KL) for a six n-channel SiNWT-based SRAM bit cell. The MuGFET simulation tool has been used to calculate the output characteristics of each transistor individually, and then these characteristics are implemented in the MATLAB software to produce the final static butterfly and current characteristics of nanowire 6T-SRAM bit cell. The demonstration of the driver to load transistors’ nanowires ratio optimizations of nanoscale n-type SiNWT-based SRAM bit cell has been discussed. In this research, the optimization of KD/KL will strongly depend on inflection voltage and high and low noise margins (NMs) of butterfly characteristics. The improvement of NMs of butterfly characteristics has been done by increasing the drain current (Ids) of the driver transistor. Also, the optimization in principle will depend on whether NMs are equal and high, and the inflection voltage (Vinf) is near to Vdd/2 values as possible. These principles have been used as limiting factors for optimization. The results show that the optimization strongly depends on the nanowire ratio, and the best ratio was KD/KL 4. The increase in KD/KL leads to a continuous increase in NMH, acceptable NML and low percentage increment of static power consumption (ΔP %) at KD/KL 4

Flood monitoring and warning systems: A brief review

Floods and excessive rainfall are unavoidable phenomena that can cause massive loss of people's lives and destruction of infrastructure. Flash floods rise rapidly in flood-prone areas, resulting in property damage, but the impact on human lives is relatively preventable by the presence of monitoring systems. Although there are many systems widely in practice by disaster management agencies in monitoring flood levels, most of these systems are limited range and sophisticated to be used and maintained. Furthermore, in most developing countries, the conventional flood gates in water canals are manually operated and suffer from the lack of real-time monitoring of water levels, leading to an overflow in the channels and flash floods. On top of that, the lacking accurate data analysis in the system that can be accessed is one of the limitations of the conventional flood monitoring and warning systems (FMWS). Therefore, in this paper, we have explored and reviewed the existing methods of flood monitoring and emphasizing their structure and sensing techniques. We have also classified and compared their advantages and limitations and accordingly suggested new solutions and improvements by utilizing new technologies based on the Internet of Things. This paper introduces a detailed mini-review of sensing methods in the existing flood systems as reported in previous studies to serve as a quick guide to researchers who are engaging in this field. Based on the review, conclusions have been draw

Design and implementation of solar-powered with IoT-Enabled portable irrigation system

This paper proposes a solar-powered portable water pump (SPWP) for IoT-enabled smart irrigation system (IoT-SIS). A NodeMCU microcontroller with a Wi-Fi interface and soil moisture, temperature, and humidity sensors are exploited to monitor and control the water pump and build an IoT-based irrigation system. The proposed irrigation system updates the gathered information from sensors (moisture, temperature, and humidity) using an integrated algorithm to the Blynk IoT cloud in real-time. Farmers can access this information and control the water pump accordingly via a user-friendly interface using their smartphones. The portable and eco-friendly water pump is powered via a solar panel and can be controlled using Blynk mobile application, which is also used to monitor the surroundings. The fabricated pump is inspired by wheeled travel luggage and is equipped with a water filter and multi-nozzles sprayer. The developed solar-based water pump has managed to save electricity and mitigate operational costs. Furthermore, the integration of the IoT concept has facilitated real-time monitoring and control of the pump; thus, enhancing the water usage efficiency and enabling convenient farming operations. The system functionality has been practically tested in a real environment, and its performance has been evaluated

Effects of downscaling channel dimensions on electrical characteristics of InAs-FinFET transistor

In this paper, we present the impact of downscaling of nano-channel dimensions of Indium Arsenide Fin Feld Effect Transistor (InAs- FinFET) on electrical characteristics of the transistor, in particular; (i) ION/IOFF ratio, (ii) Subthreshold Swing (SS), Threshold voltage (VT), and Drain-induced barrier lowering (DIBL). MuGFET simulation tool was utilized to simulate and compare the considered characteristics based on variable channel dimensions: length, width and oxide thickness. The results demonstrate that the best performance of InAs- FinFET was achieved with channel length = 25 nm, width= 5 nm, and oxide thickness between 1.5 to 2.5 nm according to the selected scaling factor (K = 0.125)

A temperature characterization of (Si-FinFET) based on channel oxide thickness

This paper presents the temperature-gate oxide thickness characteristics of a fin field-effect transistor (FinFET) and discusses the possibility of using such a transistor as a temperature nano-sensor. The investigation of channel oxide thickness–based temperature characteristics is useful to optimized electrical and temperature characteristics of FinFET. Current–voltage characteristics with different temperatures and gate oxide thickness values (Tox = 1, 2, 3, 4, and 5 nm) are initially simulated, and the diode mode connection is considered to measure FinFET’s temperature sensitivity. Finding the best temperature sensitivity of FinFET is based on the largest change in current (∆I) within a working voltage range of 0–5 V. According to the results, the temperature sensitivity of FinFET increases linearly with oxide thickness within the range of 1–5 nm, furthermore, the threshold voltage and drain-induced barrier lowering increase with increasing oxide thickness. Also, the subthreshold swing (SS) is close to the ideal value at the minimum oxide thickness (1 nm) then increases and diverges with increasing oxide thickness. So, the best oxide thickness (nearest SS value to the ideal one) of FinFET under the conditions described in this research is 1 nm

Development of a smart sensing unit for LoRaWAN-based IoT flood monitoring and warning system in catchment areas

This study introduces a novel flood monitoring and warning system (FMWS) that leverages the capabilities of long-range wide area networks (LoRaWAN) to maintain extensive network connectivity, consume minimal power, and utilize low data transmission rates. We developed a new algorithm to measure and monitor flood levels and rate changes effectively. The innovative, cost-effective, and user-friendly FMWS employs an HC-SR04 ultrasonic sensor with an Arduino microcontroller to measure flood levels and determine their status. Real-time data regarding flood levels and associated risk levels (safe, alert, cautious, or dangerous) are updated on The Things Network and integrated into TagoIO and ThingSpeak IoT platforms through a custom-built LoRaWAN gateway. The solar-powered system functions as a stand-alone beacon, notifying individuals and authorities of changing conditions. Consequently, the proposed LoRaWAN-based FMWS gathers information from catchment areas according to water level risks, triggering early flood warnings and sending them to authorities and residents via the mobile application and multiple web-based dashboards for proactive measures. The system's effectiveness and functionality are demonstrated through real-life implementation. Additionally, we evaluated the performance of the LoRa/LoRaWAN communication interface in terms of RSSI, SNR, PDR, and delay for two spreading factors (SF7 and SF12). The system's design allows for future expansion, enabling simultaneous data reporting from multiple sensor monitoring units to a server via a central gateway as a network

Performance analysis of image transmission with various channel conditions/modulation techniques

This paper investigates the impact of different modulation techniques for digital communication systems that employ quadrature phase shift keying (QPSK) and quadrature amplitude modulation (16-QAM and 64-QAM) to transmit images over AWGN and Rayleigh fading channels for the cellular mobile networks. In the further steps, wiener and median filters has been adopted to the simulation are used at the receiver side to remove the impulsive noise present in the received image. This work is performed to evaluate the transmission of two dimensional (2D) gray-scale and color-scale (RGB) images with different values from signal to noise ratios (SNR), such as; (5, 10 and 15) dB over different channels. The correct conclusions are made by comparing many of the observed Matlab simulation results. This was carried out through the results that measure the quality of received image, which is analyzes in terms of SNRimage peak signal to noise ratio (PSNR) and mean square error (MSE)

Design and Implementation of Portable Smart Wireless Pedestrian Crossing Control System

Walking is a daily activity that requires an appropriate crosswalk as a key part of the provision of safe transportation infrastructure. In this paper, we design and develop a portable smart wireless control system for pedestrian crossing areas to manage the traffic automatically and allow the pedestrian, like school children, to cross the road safely and effortlessly. The system incorporates the concept of smart sensing to detect the presence of pedestrians and in turn, automatically controls the crosswalk traffic lights. The system composes of two Arduino microcontrollers, two infrared PIR motion sensors, and a bidirectional wireless communication link based on Bluetooth for mitigating wiring installation and transmitting the signal among traffic light units on both roadsides. The system is fabricated and implemented as a portable LED-based traffic light testbed. The developed system is tested and validated in a real environment with a 6 m road width on the university campus. According to the obtained results, the system worked effectively and fulfilled the design criteria where the communication between both sides lights is successfully functioning and the PIR sensors can accurately detect the existence of pedestrians. The developed system is cost-effective, energyefficient, easy to install, and maintenance-free

Development of a smart sensing unit for LoRaWAN-based IoT flood monitoring and warning system in catchment areas

This study introduces a novel flood monitoring and warning system (FMWS) that leverages the capabilities of long-range wide area networks (LoRaWAN) to maintain extensive network connectivity, consume minimal power, and utilize low data transmission rates. We developed a new algorithm to measure and monitor flood levels and rate changes effectively. The innovative, cost-effective, and user-friendly FMWS employs an HC-SR04 ultrasonic sensor with an Arduino microcontroller to measure flood levels and determine their status. Real-time data regarding flood levels and associated risk levels (safe, alert, cautious, or dangerous) are updated on The Things Network and integrated into TagoIO and ThingSpeak IoT platforms through a custom-built LoRaWAN gateway. The solar-powered system functions as a stand-alone beacon, notifying individuals and authorities of changing conditions. Consequently, the proposed LoRaWAN-based FMWS gathers information from catchment areas according to water level risks, triggering early flood warnings and sending them to authorities and residents via the mobile application and multiple web-based dashboards for proactive measures. The system's effectiveness and functionality are demonstrated through real-life implementation. Additionally, we evaluated the performance of the LoRa/LoRaWAN communication interface in terms of RSSI, SNR, PDR, and delay for two spreading factors (SF7 and SF12). The system's design allows for future expansion, enabling simultaneous data reporting from multiple sensor monitoring units to a server via a central gateway as a network

Performance analysis of image transmission with various channel conditions/modulation techniques

This paper investigates the impact of different modulation techniques for digital communication systems that employ quadrature phase shift keying (QPSK) and quadrature amplitude modulation (16-QAM and 64-QAM) to transmit images over AWGN and Rayleigh fading channels for the cellular mobile networks. In the further steps, wiener and median filters has been adopted to the simulation are used at the receiver side to remove the impulsive noise present in the received image. This work is performed to evaluate the transmission of two dimensional (2D) gray-scale and color-scale (RGB) images with different values from signal to noise ratios (SNR), such as; (5, 10 and 15) dB over different channels. The correct conclusions are made by comparing many of the observed Matlab simulation results. This was carried out through the results that measure the quality of received image, which is analyzes in terms of SNRimage peak signal to noise ratio (PSNR) and mean square error (MSE)