Bulletin of Electrical Engineering and Informatics
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Soil moisture estimation using ground scatterometer and Sentinel-1 data
Get PDFSoil moisture (SM) is a crucial criterion for agronomics and the management of water resources, particularly in areas where the socio-economic status and significant source of income depend upon agriculture and related sectors. This paper intends to estimate SM over the vegetative area using a generalized regression neural network (GRNN) and ground scatterometer and compare the results with SM retrieved using Sentinel-1 data. At the same time, random forest regression (RFR) and support vector regression (SVR) models are used for SM estimation. Correlation analysis results concluded that L-band HV-polarization at 300 incidence angle showed the highest correlation with the measured field parameters. This study investigated backscattering coefficients, VV/VH polarization ratio and polarization phase difference over wheat’s entire growth phase to estimate SM. The results indicate that the GRNN with backscattering coefficients and polarization ratio provided the highest accuracy compared to the random forest (RF) and SVR with the root mean square error of 0.093 over the Yavatmal District, Maharashtra, India
Smart irrigation with crop recommendation using machine learning approach
Get PDFIncreasing crop yield with sustainable growth is the primary requirement for farmers with a growing population. Effective management and conservation of depleting natural resources is a priority task. Decrease in manpower due to migrating population has forced automation in agriculture. In this work, an automatic water irrigation and an effective crop recommendation system is proposed. Gypsum blocks based soil sensor is used to measure dielectric permittivity associated with the tested soil. The water-potential present in soil, along with potassium (K), nitrogen (N), phosphorus (P), potential of hydrogen (pH) helps to quantify the soil nutrients available and the suitable crop that can be considered for harvesting in a specified demography and environment. Sensory data indicating soil quality obtained is used to recommend crops by utilizing machine learning approaches. Telegram application is linked to the recommendation model to assist decision making and to ensure farmer-friendliness by sending notifications periodically
Efficient k-way partitioning of very-large-scale integration circuits with evolutionary computation algorithms
Get PDFThe standardization of very-large-scale integration (VLSI) physical architecture for VLSI chips and multichip platforms is now in its early stages of development. The purpose of VLSI partitioning is to divide the circuit into numerous smaller circuits with few connections in between. Partitioning is the fundamental problem in circuit design and division. The efficient method of evolutionary computation may be used to tackle the partitioning problem in VLSI circuit design. It provides a heuristic approach to solve this problem by exploring the solution space and incrementally improving the quality of the solutions. In order to obtain the shortest wire length (WL), area, and connections, an evolutionary optimized simulated annealing memetic algorithm (OSAMA) that incorporates one or more local search phases inside its evolutionary cycle was developed
Automated lighting design in the classroom
Get PDFLamp automation is utilized to adjust the lighting in the classroom by adjusting to the level of sunlight intensity outside the classroom. The light intensity will be adjusted to the utilization of lights as indicated by the need to enlighten a room. Therefore, this research aims to depict the design of a light intensity measurement system using a BH1750 sensor that will be carried out to measure the intensity of sunlight in units of light (lux). The signal from the sensor will be transmitted to a mini pc which functions to process measurement data and display it on the graphical user interface (GUI). As a result, the sensor will instruct the dimmer as an actuator to control the classroom lights according to the lighting from the sun. This system is already installed in the classroom and can save energy around 35 kWh a year
Revisiting 5G quality of service in Bangkok metropolitan region: BTS Skytrain station areas
Get PDFThis article compares two of the leading mobile network operators (MNOs) in Thailand’s telecom market in terms of the service quality of Thailand’s fifth generation (5G) networks. The following three factors: download speed, upload speed, and latency, which are frequently considered to be indicators of the quality of Internet networks, were examined. The researchers employed the test results to determine the quality of service (QoS) that was achieved by comparing newly collected data to data that had previously been examined utilizing the same format and application in the middle of May 2021. The average download speed decreased from 196.4 Mbps in 2021 to 140.4 Mbps in 2023, while the average upload speed dropped from 62.6 Mbps in 2021 to 52.0 Mbps in 2023. Furthermore, the average latency increased from 14.9 ms in 2021 to 23.3 ms in 2023. These results show a considerably enhanced service although the test region in this study only comprised BTS stations. Furthermore, this was the case even though the test area in this study only encompassed a small percentage of the total population
A comprehensive survey on several fire management approaches in wireless sensor networks
Get PDFThe majority of the fires are activated through environmental reasons although a minority of them are self-activated. To detect fires several safety systems were introduced. There are wired systems, cameras, satellite systems, and bluetooth feasible to provide a complete image of the world but after a long search period. These systems are not perfect since it prevents fire from finding just at the time, the fire initiates. But, recent technological development in wireless sensor networks (WSN) has spread out its fire detection application. A comprehensive survey on several fire management approaches in WSN propose to discuss various fire detection approaches like early fire detection, energy efficient fire detection, mobile agent-based fire detection, unmanned aerial vehicle (UAV)-based fire detection, threshold-based fire detection, machine learning based fire detection and secure fire detection approaches. Moreover, the comprehensive tabular study of the fire management technique is given that will assist in the suitable selection of approaches to be applied for the detection of fire. Furthermore, WSN uses the clustering method to minimize redundant dataandsecure fire detection approaches collect authenticated data related to fire detection. Early fire detection approaches detects the fire early. Machine learning algorithm detects the fire efficiently
Empowering customer satisfaction chatbot using deep learning and sentiment analysis
Get PDFThe rapid advancement of technology holds great promise for various types of users, clients, or service providers. Intelligent robots, whether virtual or physical, can simplify the reservation process. With the development of machines and processing tools, natural language processing (NLP) and natural language understanding (NLU) have emerged to help people comprehend spoken language through machines. In order to facilitate seamless human-machine interaction, we aim to address customer needs through a chatbot. The objective of this paper is to incorporate sentiment analysis techniques with deep learning algorithms to cater to customers’ needs during message exchanges. This study aims to create an intelligent chatbot to engage customers during their routine operations and offer support. In addition, it offers to companies a manner to detect sarcastic messages. The proposed chatbot utilizes deep learning techniques to predict users’ intentions based on the questions asked and provide a helpful and convenient answer. A new chatbot for the customer is presented to overcome with challenges related to a wrong statement like sarcastic one and feedback towards user messages. A comparison between deep and transfer learning gives a new insight to include sentiments and sarcasm detection in the conversion process
Refining disparity maps using deep learning and edge-aware smoothing filter
Get PDFStereo matching algorithm is crucial for applications that rely on three-dimensional (3D) surface reconstruction, producing a disparity map that contains depth information by computing the disparity values between corresponding points from a stereo image pair. In order to yield desirable results, the proposed stereo matching algorithm must possess a high degree of resilience against radiometric variation and edge inconsistencies. In this article convolutional neural network (CNN) is employed in the first stage to generate the raw matching cost, which is subsequently filtered with a bilateral filter (BF) and applied with cross-based cost aggregation (CBCA) during the cost aggregation stage to enhance precision. Winner-take-all (WTA) strategy is implemented to normalise the disparity map values. Finally, the resulting output is subjected to an edge-aware smoothing filter (EASF) to reduce the noise. Due to its resistance to high contrast and brightness, the filter is found to be effective in refining and eliminating noise from the output image. Despite discontinuities like adiron's lost cup handle or artl's shattered rods, this approach, based on experimental research utilizing a Middlebury standard validation benchmark, yields a high level of accuracy, with an average non-occluded error of 6.79%, comparable to other published methods
BER estimation for STBC-MC-DS-CDMA-4 antennas system by varied wavelet-carriers features via AWGN-flat channels
Get PDFThis paper improves the bit error rate (BER) of the modern communication system by taking into account the effect of the wavelet shape and the number of carriers on the performance of the space time block code multi-carrier direct sequence code division multiple access (STBC-MC-DS-CDMA). Here the transmitter is moved with speeds 2 km/hr, 45 km/hr and 100 km/hr via Rayleigh flat fading channel. Here, 2 antennas are employed at the receiver to mitigate the multipath signal influence. The system’s orthogonal frequencies are generated using Haar, Daubechies 4, Symlets 4, Cohen-Daubechies-Feauveau 1.1 with 9.7 and B-spline 3. The number of used carriers is 128, 512, and 1,024. Quadrature phase shift key (QPSK) is used with cyclic prefix 1/16 and a bandwidth of 20 MHz. traditional fast fourier transform (FFT) system is compared to the proposed discrete wavelet packet transform (DWPT) to show the BER enhancements. The space-time block coding (STBC) is used to enhance system cabability in error corection. The proposed system shows significant improvement in BER, so that, it reaches to the same BER when using FFT but with less signal to noise ratio (SNR), which interns reduce the power consumed within the system and the cost
Solar photovoltaic integrated load frequency control of power system using variable structure fuzzy controller
Get PDFThe incorporation of renewable energy sources into modern power systems is on the upswing, intending to produce and deliver cost-efficient electricity to meet the ever-increasing demands of today’s world. Solar energy stands out as a plentiful and robust solution for meeting current electricity requirements. However, integrating solar photovoltaic (PV) generated power into the contemporary power system introduces complexity, necessitating the development of suitable control design to ensure effective regulation of load frequency control (LFC). This research paper concentrates on the mathematical modeling and integration of solar PV generated electricity into a hydrothermal system. In addition, this study also evaluates the performance of the variable structure fuzzy (VSF) control with reduced rule base for hydrothermal system concerning varying degrees of disturbances in one or in both regions of the power system. Moreover, the research reveals that the integration of PV power into hydro-thermal systems can improve the LFC outputs and mitigate system deviations in the face of different disturbance scenarios