This paper presents a density-based traffic light signal system that performs timing signal that changes automatically based on the amount of traffic at each of its intersections. However, as traffic congestion is a pertinent problem on all of Ahmadu Bello University’s (ABU) gates, it is time to advance from the traditional technique to an automated system that has self-decision capabilities. The current technique used on the traffic system is based on the traditional technique, which works based on time scheduling; this system is inefficient if one lane is operational while the others are not operational. The intelligent traffic control was prototyped in order to solve this perennial problem of ABU’s gate. When there is a high density on one lane of the intersection, it causes a longer waiting time on the other lanes than the regular permitted time. As a result, a process was designed through which the time periods for the green and red lights were assigned based on the traffic densities on each of the lanes at that time. Infrared (IR) sensors were used to perform this task. The Arduino Uno Microcontroller was used for allocating the glowing period of green lights once density had been calculated. Sensors were used for monitoring the presence of vehicles and communicating information to the microcontroller, which determines the duration for which a signal will change or a flank will remain open. Also displayed is the operating principle of the density-based traffic signal control system, which shows the prototype’s efficiency.

This research presents the development of an autonomous floor mopping robot controller using an android application. The mopping robot was designed to solve the technical challenges that is faced in the daily chores of cleaning in order to aid the convenience of most people who are extremely busy in their chores. The robot was controlled using a mobile app via a smart phone with the aid of a Bluetooth module, in which it receives the guide on the path to navigate. The robot performed task of wet and dry cleaning, which in the case of the dry cleaning, it sweeps the dirt's and collect the dust, while for wet cleaning, the robot sprayed water in the affected area, and moped the area. The robot executed this task successfully while reducing the cost of labor, time and provides an efficient way of cleaning.

This research presents the development of an android-based, voice-controlled autonomous robotic vehicle. This article was developed in a way that the robotic vehicle was controlled using voice commands. An android application combined with an android microcontroller was used to achieve this task. The connection between the android app and the autonomous vehicle was facilitated using Bluetooth technology. The vehicle was controlled with either the aid of the buttons on the app, or by spoken commands from the user. The movement of the vehicle was achieved by using four DC motors connected with the microcontroller at the receiver side. The commands from the app were converted into digital signals using the Bluetooth RF transmitter within a specific range (of around 100 m) of the autonomous vehicle. At the receiver end, the data gets decoded by the receiver and is fed to the microcontroller which moves the DC motors of the vehicle for navigation. The voice-controlled autonomous robotic vehicle performed navigational tasks by listening to the commands of the user. This was achieved by converting voice commands into text strings which are readable by the Arduino microcontroller on the android app in order to control the navigation of the robot. The vehicle was tested under different conditions and was observed to perform better using this technique and also the results were satisfactory when compared with other previous research that has been conducted in this area.

This paper proposes the performance comparison of a linear quadratic regulator (LQR) controller for the ball and beam system (BBS). The BBS is a standard benchmark control system, which has two degree-of-freedom (2 DOF). It is an open loop and a highly nonlinear unstable system. This makes its parameter difficult to be estimated accurately, hence designing a controller for it is a challenging task. MatheThe BBS was modelled using Euler–Lagrange modeling technique, while the LQR controller was used for the stabilization of the ball on the beam. Simulation was done in MATLAB/Simulink 2022b environment, and the results simulated showed that for the two weighting matrices (Q and R), the state weighting matrix had a higher penalty on the ball displacement, ball velocity, beam angle, and beam angular velocity at lower values of Q. For the state weighting matrix had a better effect of penalty performance on the BBS with lower values. Also, as the diagonal element of the state weighting matrix Q increases from 0.1 to 20, the values of the optimal controller K increase, the reduced Ricatti matrix P increases, and the estimated eigenvalues E reduce. This implies that the ball displacement, ball velocity, beam angle, and beam angular velocity are better at lower values of Q.

The following topics are dealt with: Internet; cellular radio; microcontrollers; cloud computing; quality of service; security of data; antenna radiation patterns; power engineering computing; distribution networks; Internet of Things.

This paper presents a weighted Artificial Fish Swarm Algorithm (wAFSA) based model for placement of Distribution Static Compensator (DSTATCOM) in distribution systems. The bus injected to branch current technique (BIBC) has been employed for direct power flow analysis. A multi-objective function to minimize active losses and bus voltage deviation subject to satisfying the network constraints has been formulated for use in the wAFSA. The approach is evaluated on the Standard IEEE 33-bus test network and validated against harmony search algorithm (HSA) technique for steady-state constant load analysis. The results demonstrated significant improvement of the wAFSA model with a 28.96% reduction in total active power loss and a 43.11% improvement in overall system voltage profile. Against the HSA, the wAFSA approach achieved a 0.27% loss reduction and 5.15% voltage profile improvement.