Current Issue : July-September Volume : 2023 Issue Number : 3 Articles : 5 Articles
This study addresses the underlying challenges of computer vision adoption in the Kenyan agricultural sector and how to solve these hurdles to commercialize this technology. Technological advancements have revolutionized the agriculture sector, where artificial intelligence enhances yields, mitigates losses, and manages natural resources, leading to increased productivity. Kenya is still lagging in the commercialization of computer vision to improve its agricultural sector, which is the largest source of GDP. Kenya has remarkable skills and expertise in artificial intelligence that can support artificial intelligence implementation; the government policies, data availability, and high cost incurred in starting a computer vision company are problematic. Through better government policies on subsidies and data, research and development investments, and AI forums, Kenya will solve the challenges of adopting computer vision. While computer vision has the potential to revolutionize the agricultural industry by improving crop yield, detecting diseases, and increasing efficiency, there are several barriers to its adoption, including inadequate infrastructure, lack of technical expertise, and limited funding. This study aims to identify the challenges hindering the implementation of computer vision technology in the Kenyan agricultural sector and propose potential solutions to address these challenges....
This article aims to explore an effective method for reducing vehicle collisions at unsignalized intersections. First, a monocularbinocular vision switching system is built to enable machine vision-based detection of obstacle vehicles in the left and right front directions. Then, the motion state and trajectory of each obstacle vehicle are predicted, and the intersection points of the trajectories of the obstacle vehicle and the ego vehicle are calculated. On this basis, a cross-conflict judgment model based on trajectories and collision times and a safety assessment model based on safety distance are established. Finally, the conflict judgment and safety assessment for the obstacle vehicles are simulated. The results of the simulation demonstrate that the monocular-binocular vision switching system proposed in this article can achieve a detection accuracy of 95%, a ranging accuracy of 96%, and a cross-conflict detection accuracy of 97%, while ensuring a maximum detection area, which can meet the requirements of traffic safety assurance at unsignalized intersections....
In chemical processes, packed columns are frequently employed in various unit operations. However, the flow rates of gas and liquid in these columns are often constrained by the risk of flooding. To ensure the safe and efficient operation of packed columns, it is crucial to detect flooding in real time. Conventional flooding monitoring methods rely heavily on manual visual inspections or indirect information from process variables, which limit the real-time accuracy of results. To address this challenge, we proposed a convolutional neural network (CNN)-based machine vision approach for non-destructive detection of flooding in packed columns. Real-time images of the packed column were captured using a digital camera and analyzed with a CNN model, which was been trained on a dataset of recorded images to identify flooding. The proposed approach was compared with deep belief networks and an integrated approach of principal component analysis and support vector machines. The feasibility and advantages of the proposed method were demonstrated through experiments on a real packed column. The results showed that the proposed method provides a real-time pre-alarm approach for detecting flooding, enabling process engineers to quickly respond to potential flooding events....
Anthropometric measurements are essential in various fields, such as sports, the automotive industry, clothing, health care, biomechanics, ergonomics, and gait analysis. However, the data collection process for these measurements is costly and time-consuming, and the data collected are not always precise and accurate. In this paper, some of the most widely reported machine vision systems (MVSs) are evaluated to determine the anthropometric length of body segments (BSs) used in gait analysis. The aim is to evaluate the performance of the MVSs and identify the most appropriate vision approach, in terms of accuracy, cost, speed, and computing performance. For this purpose, five BSs of the lower limb were selected and measured using both the MVS and the conventional manual anthropometric measurement (MAM) techniques. The results show that the MVSs represent an excellent alternative to measure the anthropometric parameters corresponding to the BSs, with some advantages in terms of sampling process time, precision, and equipment requirements....
The aim of this work was to evaluate how 1-methylcyclopropene (1-MCP) treatment affects appearance of plum fruit. Fruit of ‘Angeleno’ and ‘Topend’ cultivars were treated with 625 ppb gaseous 1-MCP at 1 ◦C for 24 h after harvest. Samples without treatment, called control, and those subjected to the treatment were stored at 1 ◦C for 8 weeks (Topend) and 10 weeks (Angeleno). The subgroup of initial samples and those withdrawn from cold storage were also measured after 7 d storage at 20 ◦C. According to measured parameters of ethylene, CO2 production, firmness, and total soluble solids content, there was a clear difference between 1-MCP- treated and control samples for both cultivars. Color attributes of hue angle and saturation changed significantly during storage, especially for flesh color measured on fruit cut in half. The comparison revealed that saturation responded more sensitively to changes. Firmness correlated significantly with color attributes, and flesh saturation reached the highest value of Pearson’s correlation of r = 0.608 (p < 0.01) and Spearman’s rank correlation of ρ = 0.636 (p < 0.01). The specific plum color was also evaluated with a normalized blue value, which obtained significant linear correlation with firmness (r = −0.7414, p < 0.001). There was significant difference between cultivars in terms of surface color and its correlation with firmness as Pearson’s correlation obtained r = 0.833 (p < 0.001) for ‘Topend’ and r = 0.556 (p > 0.05) for ‘Angeleno’....
Loading....