The conventional voting scheme employs paper-based ballot to verify votes. This voting scheme is insecure due to the attributed shortcomings including ballot stuffing, ballot snatching and voter's impersonation. In this paper, we present the design and development of secure e-voting to ensure a free, fair and credible election where the preference of electorate counts. This proposed system solves the authentication, integrity and confidentiality security issues of e-voting in kiosk and poll site evoting scenarios using unimodal fingerprint biometrics and Advanced Encryption Standard based Wavelet based Crypto-watermarking Approach. The developed system solves: The possibility of blundering voter's authentication, integrity and confidentiality of vote stored in the server. The results after qualitative evaluation of the system with antiwatermarking detectors revealed that the developed secure e-voting system could serve as a platform for the delivery of credible e-election in developing countries with significant digital divides.
The amount of feed dispense to match fish appetite plays a significant role in increasing fish cultivation. However, measuring the quantity of fish feed intake remains a critical challenge. To addressed this problem, this paper proposed an intelligent fish feeding regime system using fish behavioral vibration analysis and artificial neural networks. The model was developed using acceleration and angular velocity data obtained through a data logger that incorporated a triaxial accelerometer, magnetometer, and gyroscope for predicting fish behavioral activities. To improve the system accuracy, we developed a novel 8-directional Chain Code generator algorithm that extracts the vectors representing escape, swimming, and feeding activities. The set of sequence vectors extracted was further processed using Discrete Fourier Transform, and then the Fourier Descriptors of the individual activity representations were computed. These Fourier Descriptors are fed into an artificial neural network, the results of which are evaluated and compared with the Fourier Descriptors obtained directly from the acceleration and angular velocity data. The results show that the developed model using Fourier Descriptors obtained from Chain Code has an accuracy of 100%. In comparison, the developed classifier using Fourier Descriptors obtained directly from the fish movements acceleration, and angular velocity has an accuracy of 35.60%. These results showed that the proposed system could be used in dispensing feeds successfully without human intervention based on the fish requirements. INDEX TERMS Accelerometer, artificial neural network, aquaculture, chain code, fish, fish activities, fish feeding system, Fourier descriptor, IoT devices.
The application of precision agriculture in farming practices results in higher yield and productivity with lower costs. Several works have applied this concept to poultry farming in an attempt to reduce human involvement, stress, fatigue, wastage of poultry feed as well as provided a high return on investment. A number of these systems lack control techniques to improve the system performance. A few works exist that implemented control techniques to improve system response, but different systems were implemented and therefore, a comparison cannot be made. In this paper the performance comparison of the Fuzzy Logic Controller (FLC) and the PID Controller on the Poultry Feed Dispensing System was evaluated in a quest to determine the more efficient and effective controller. The system was modelled and simulated using MATLAB SIMULINK and the performance was evaluated based on the rise time, settling time, overshoot and Integrated Absolute Error (IAE). The results showed that the system implemented with the PID and FLC performed better than the system without a control technique. The PID gave a faster system response than the FLC in the solid feed subsystem with a difference in rise time, settling time and IAE of 9.72 seconds, 11.68 seconds and 4.74 respectively. The FLC performed better in the liquid feed subsystem with a difference in rise time, settling time, overshoot and IAE of 9.22 seconds, 33.07 seconds, 13.92% and 7.18 respectively. This shows that the PID controller is more suitable in the solid feed subsystem and the FLC is more effective in the liquid feed subsystem.
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