The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is crucial for enhancing urban development, environmental monitoring, and advancing smart city governance. LiDAR, known for its high-resolution 3D data capture capabilities, paired with AI, particularly deep learning algorithms, facilitates advanced analysis and interpretation of urban areas. This combination supports precise mapping, real-time monitoring, and predictive modeling of urban growth and infrastructure. For instance, AI can process LiDAR data to identify patterns and anomalies, aiding in traffic management, environmental oversight, and infrastructure maintenance. These advancements not only improve urban living conditions but also contribute to sustainable development by optimizing resource use and reducing environmental impacts. Furthermore, AI-enhanced LiDAR is pivotal in advancing autonomous navigation and sophisticated spatial analysis, marking a significant step forward in urban management and evaluation. The reviewed paper highlights the geometric properties of LiDAR data, derived from spatial point positioning, and underscores the effectiveness of machine learning algorithms in object extraction from point clouds. The study also covers concepts related to LiDAR imaging, feature selection methods, and the identification of outliers in LiDAR point clouds. Findings demonstrate that AI algorithms, especially deep learning models, excel in analyzing high-resolution 3D LiDAR data for accurate urban feature identification and classification. These models leverage extensive datasets to detect patterns and anomalies, improving the detection of buildings, roads, vegetation, and other elements. Automating feature extraction with AI minimizes the need for manual analysis, thereby enhancing urban planning and management efficiency. Additionally, AI methods continually improve with more data, leading to increasingly precise feature detection. The results indicate that the pulse emitted by continuous wave LiDAR sensors changes when encountering obstacles, causing discrepancies in measured physical parameters.

Today, the presentation of a three-dimensional model of real-world features is very important and widely used and has attracted the attention of researchers in various fields, including surveying and spatial information systems, and those interested in the three-dimensional reconstruction of buildings. The building is the key part of the information in a three-dimensional city model, so extracting and modeling buildings from remote sensing data is an important step in building a digital model of a city. LiDAR technology due to its ability to map in all three modes of one-dimensional, two-dimensional, and three-dimensional is a suitable solution to provide hyperspectral and comprehensive images of the building in an urban environment. In this review article, a comprehensive review of the methods used in identifying buildings from the past to the present and appropriate solutions for the future is discussed.

The purpose of the study was to examine the knowledge base of students in the Assin Manso Senior High School in the central region of Ghana. A qualitative method was used in this study. The population of the study comprised students from Assin Manso senior high school in the Central Region of Ghana. Purposive sampling technique was employed to select forty (40) respondents for this study. The forty (40) respondents consisted of all Students Representative Councils (SRC) members in the school. Each class has a representation in the study. The main instrument for data collection was interview guide. The data collection was done using Interpretative Phenomenological Analysis (IPA). The qualitative data was analysed by the use of the interpretative technique based on the themes arrived at during the interview. The themes were related to the research question. The study revealed that honesty is being loyal to a colleague, covering them up and standing by them as well. The study also indicated that honesty depict “we feeling” or “solidarity”, so to them any students who does the opposite is considered to be dishonest. It is recommended that, Students who obey the school rules and regulations should be motivated by the school authorities in order to encourage the other students to do same. It is also recommended that parents and educators, should all advocate the teaching of moral values in our schools to instil in students the benefits that honest brings to them, the school, the family, community and the country as a whole.

The right to the environment and the research right are human rights that must be protected. The right of individuals to a healthy environment is part of the human rights that are increasingly threatened by human activities. This right is a prominent example of solidarity rights and a prerequisite for realizing many human rights. Exercising this right requires a level of development that provides the basis for further environmental degradation. The activities of academic researchers in the direction of progress and development can pave the way for environmental damage. This article discusses when a researcher causes harm in conducting academic research. The need to compensate and support the researcher in conducting their research contrasts these two rights; Therefore, it is necessary to look for ways of compensation that make possible the simultaneous protection of these two rights. Because according to Article 21 of the Stockholm Declaration and Article 2 of the Rio Declaration, governments are responsible for ensuring that their activities do not lead to environmental damage. The key role of governments in resolving this conflict and helping to promote academic research, reducing harm, and trying to prevent this kind of harm is obvious. In this article, we intend to resolve this conflict by examining the principles of human rights, the right to research, and the right to the environment and to examine Iran’s legal approach in this regard.

Sport is an art form. Every athlete thinks, creates, obeys rules, plans, and produces tangible results. Like most art forms, basketball for learning, monitoring, and understanding the sport requires all five senses. With the same logic by which an architect plans to build a building, the basketball team prepares for the game mode, the systems, which they will have in a match. In summary the players and the coaching staff think before they do. For this reason, in basketball it is important to create a philosophy and a system of values in the team. Values such as trust, solidarity, cooperation, ambition, consistency are important for building the mindset among stakeholders for the successful course of the team and for titles. Finally, sport produces knowledge. Basketball is an evolving and progressive sport. Adapting to modern requirements, studying, and monitoring new trends. For example, the specialization of players in Shoot, in speed in, power, strong, results in an increase in the ability of players to man-to-man attacks. On the other hand, the defensive function of both individual and team needs to deepen the proper treatment of powerful offensive players.