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Wireless communication, in its infrastructure nature, faces many challenges such as fading, data coverage, and interference issues. Therefore, High-Fidelity or (Li-Fi) is utilized due to its ability to naturally provide high-density wireless data coverage in closure’s particularly helpful for application(s) in some areas while the radio interference conditions are concern. This article illustrates an advanced Li-Fi approach performing high-speed data transmission between two Personal Computers (PCs) utilizing the Arduino Nano-based technique. In the experimental phase, data is mainly used to be transmitted over red laser diode (630 nm) through (30 cm) in distance, a distance of 30 cm, achieving a high peak speed reach to about (512Bps). The proposed approach performance is computed by evaluating the most important and related metrics like Signal-to-Noise Ratio (SNR), Bit-Error-Rate (BER), and influence of throughput on input data over various light circumstance. The proposed approach mainly utilizes a keypad as a user input and two related detection models for both a solar cell and a photodetector in order to make a powerful comparison in terms of performance. the results showed that when the photodetector applies a higher-detection efficiency (via BER enhancement which reaches to 20% over solar-cell), the solar-cell clarify outstanding power and cost-activity. The mentioned findings are propped by elaborated statistical-analyses and MATLAB simulation to design, simulate and visualize the validate functionalities of the robustness and scalability properties of the proposed Li-Fi approach.

In image detection processes where there is a variation in brightness between pixels, techniques are required to obtain optimal and adaptable threshold values for these variations. Therefore, a comparison between the binary thresholding technique and the adaptive method of Otsu is made, in videos with dynamic and static background, weighing the response time of the algorithm, memory used, requirement of the central processing unit and hits in the detections, in the languages of Python and M (Matlab). The techniques in Python present better results in terms of response time and memory space; while, when using Matlab, the lowest percentage of machine requirement is presented. Also, the Otsu method improves the percentage of hits in 12.89 % and 11.3 % for videos with dynamic and static background, with respect to the binary thresholding technique.

The need for urban communities to consume vegetables is increasing. This has caused people to start cultivating vegetables using hydroponic techniques. However, due to their busy activities, they do not have enough time to monitor and control hydroponics, which must always be in ideal conditions. This paper designs and implements an Internet of Things-based monitoring system to help hydroponic owners monitor their hydroponics anywhere and anytime. The built system requires a monitoring device assembled using a NodeMCU ESP8266 microcontroller, a pH detection detector sensor, and a DHT22 temperature and humidity sensor. This system uses the Mamdani Fuzzy Logic algorithm to determine warnings to be displayed on the application interface when the water pH, temperature, and humidity are in certain conditions. The Mamdani Fuzzy Logic algorithm can interpret environmental data into a warning that humans can easily understand, even if they lack technical expertise. In addition to being able to help monitor, this system also allows owners to find out what elements need to be added or changed for their hydroponic place. Our evaluation results show that the defuzzification stage in the application has high accuracy, which is 99.92%, compared to Matlab’s results.