Journal of Engineering, Technology, and Applied Science (JETAS)

Mitigating Professional Interference for Sustainable Growth in the Nigerian Construction Industry: A Comprehensive Review

2024-09-19T15:12:00+00:00

The Nigerian construction industry is a dynamic sector with various professional roles and rivalries, crucial for economic development and stability. However, professional interference can hinder its sustainable growth and expansion. A multi-faceted approach involving multiple stakeholders, including government bodies, industry associations, professionals, and the public, is needed to create an environment that promotes professionalism, accountability, and quality in the industry. Understanding the implications and consequences of professional interference is crucial for sustainable growth in the Nigerian construction industry. A qualitative research study identified the core roles of NIA, NIQS, and NSE and the causes of professional interference. According to our study, it is recommended that the Federal Republic of Nigeria create regulatory councils for professional organizations in the construction sector to define their boundaries, tasks, and obligations. Stringent regulations and enforcement of laws are necessary to prevent professionals from overlapping roles and responsibilities, to avoid potential repercussions like losing their practice licenses, tarnishing their reputation, and legal consequences under media scrutiny.

Bird Species Classification System Using Transfer Learning

2024-09-19T15:10:05+00:00

Manual recognition is limited by the observer's expertise and knowledge, which can lead to errors when observed by non-experts. The objective of this research is to create a machine learning algorithm that can accurately classify bird species based on physical features and develop a software system that includes the machine learning algorithm, allowing for efficient classification of different bird species. This research also wants to evaluate the accuracy of the approach in real-world scenarios. The methodology research uses the machine learning life cycle model and software development life cycle model. The research aims to provide a user-friendly interface that recommends bird species classifications based on uploaded images, ultimately contributing to a more accessible and informative bird identification experience. In this research, the F1-score with fine-tuning is reported as 0.8889. It is close to 1, it suggests a well-balanced performance in terms of correctly identifying positive instances which is precision, and capturing relevant positive instances which are recalled. Based on the result, the proposed system can enhance users' ability to accurately identify and classify various bird species through the utilization of a pre-trained convolutional neural network model.

Modeling and Implementation of a Hybrid Solar-Wind Renewable Energy System for Constant Power Supply

2024-08-27T04:53:36+00:00

In recent years, Uganda has significantly increased the use of renewable energy sources, particularly solar and wind power. These energy sources are especially crucial in rural and remote areas where connecting to the national grid is challenging. Renewable Energy Sources (RES) have proven to be cost-effective alternatives to traditional energy sources, which often require substantial investments in transmission and distribution networks. This study focuses on designing and implementing a hybrid renewable energy system that integrates both solar and wind power. The research successfully established a reliable and continuous power supply for the community through the combination of wind and solar energy. The hybrid power generation system operates by simultaneously monitoring solar and wind energy using an ACS712 current and voltage sensor. Controlled by a microcontroller, the system employs dual-channel relay switches to activate the power source with sufficient energy to charge the battery. The programming for this system was conducted using C++ and Arduino software. This study highlights the vast potential within the field of sustainable energy. With rapid and economical electricity production, this hybrid system paves the way toward a greener future, where our energy needs can be met in an environmentally friendly manner.

Refill Water Management System Using an IoT-Based Water Flow Sensor

2024-09-21T09:12:34+00:00

The primary and crucial use of water is as a drink. It is crucial for meeting the fluid needs of the human body. Dying from dehydration can occur when 15% of body weight is lost from not having enough water. Currently, numerous water refill points are accessible, sourced from both boreholes and mountain springs. Water is traditionally measured in transportation cars by filling the container without tracking the water input and output. This study aims to create a reusable water-filling control device that will track the inflow and outflow of water in the storage tank with the help of a Water Flow Sensor. The data obtained is based on analysis using the Arduino Uno in determine the volume of water, which is sent to the web server via the ESP8266 Wifi Module, providing the water volume information is shown directly on the management system app. Real-time viewing of the water volume data from the water flow sensor is possible in the refill water management app. After carrying out experiments; the 1,500 ml experiment showed the highest accuracy at 99.47%. The deviation of the 1,500 ml experiment is only 0.53%, showcasing the potential benefits of an automated water management system.

Application of Wireless Sensor Network in Monitoring Quality of Irrigation Water

2024-09-19T15:04:32+00:00

One of the things that needs to be considered to maximize the quantity and quality of agricultural products is the maintenance of irrigation water. Farmers still difficult to monitor the quality of irrigation water due to the high cost of laboratory tests and the need for real-time monitoring of water discharge into rice fields. Some of the impacts of not maintaining irrigation water in recent years include the roots rotting easily. This research aims to create a system that can detect and monitor the quality of irrigation water that will flow into rice fields according to water quality criteria in real time with wireless sensor network technology. In this research, the parameters of pH, conductivity, temperature, and dissolved oxygen are used to determine the quality of irrigation water quality. Based on the experiment results of two types of irrigation water; river water has good pH and conductivity values while the value of dissolved oxygen is poor, while borehole water has good pH, conductivity, and dissolved oxygen values. The calibration process was carried out under the procedures and succeeded well, characterized by sensors that can detect the quality value of irrigation water. In this research, the data from the sensors can be transferred to the server via the GSM module with a time difference between data of about 10-40 seconds. This indicates the performance of the sensor and detection system is running well.

Spatiotemporal Analysis and Mapping of Fire Incidents Using GIS Technology

2024-09-19T15:02:45+00:00

Spatiotemporal fire analysis and mapping can enable policymakers to develop effective fire management strategies that optimize the allocation of necessary resources. Efficient urban fire management requires a well-coordinated regional planning and response system. The primary objective of this paper is to analyze the spatiotemporal patterns of fire incidents in Austin, Texas, utilizing geospatial technologies. This study specifically addresses deficiencies in fire protection planning in Austin, along with the new challenges posed by the city’s rapid expansion. The fire risk and vulnerability of buildings in Austin were assessed using Geographic Information System (GIS) technology. GIS was also employed to identify potential sites for new fire stations and to optimize the design of existing stations based on fire risk assessments. This paper focuses on developing a GIS-based fire information system for the Austin Fire Department to determine the optimal route to fire incidents. The research produced a fire incidence distribution map and examined fire occurrence patterns using spatial statistical methods, including location identification, frequency analysis, and evaluation of fire hazard vulnerability and exposure. Based on the findings, the establishment of new fire stations is recommended, particularly in areas with high fire risk. The fire information system developed to identify optimal routes could be integrated with construction and cadastral inventory data to form a more comprehensive decision support system.