Introduction

Noise pollution is an environmental phenomenon that has gained increasing relevance in recent decades due to the rapid and continuous growth of urban areas and rapid industrial development.¹ Accelerated urbanisation and the expansion of industrial activity have contributed to a proliferation of noise in urban environments, which has raised the importance of addressing this problem to ensure the quality of life of the inhabitants. It refers to the excessive and constant presence of noise in the environment, generated by various anthropogenic sources such as vehicular traffic, industrial machinery in full operation, construction in progress, recreational activities with loud music and noisy public events, among others.² Noise sources are diverse and often interdependent, making mitigation a multifaceted challenge. The proliferation of vehicular traffic and industrial expansion have intensified these sources, contributing to widespread noise exposure in urban environments.³

Sources of noise pollution are classified as stationary, which include industrial facilities and airports, and mobile, which encompasses vehicular traffic and outdoor activities.⁴ These sources are interconnected and can exacerbate each other, creating a complex sound environment. For example, industrial areas can contribute to an increase in noise levels from nearby traffic and vice versa. It is important to note that noise levels can vary significantly depending on geographic location and time of day, being more intense in densely populated urban areas and during certain time zones.⁵ Noise patterns can be influenced by population density, infrastructure and economic activity. In urban areas, high concentrations of people and commercial activities can increase noise exposure, especially during rush hours. Additionally, seasonal variability and special events can add temporary noise spikes that require careful consideration in noise pollution management. In addition to anthropogenic sources, there are additional factors that contribute to aggravating noise pollution.⁶ High noise levels have significant impacts on various environments, including residential areas, parks and natural ecosystems.^7,8

At the human level, continuous exposure to noise pollution can have serious health consequences.⁹ Among the most common effects are chronic stress, sleep disturbances, cardiovascular and hearing problems, and impaired cognitive performance. In the specific case of children, early exposure to high noise levels can negatively affect language development and learning.¹⁰ Constant exposure to noise can cause anxiety and depression, affecting the quality of life and emotional well-being of people living in noisy areas.¹¹

In this context of growing concern about noise pollution, technology has emerged as a crucial ally to address various environmental problems. Web-based systems have emerged as highly effective tools for monitoring, analysing and controlling noise levels in urban environments and sensitive areas.¹² These systems, often based on sound sensors strategically located at key points in the city, can collect real-time data on noise levels at different locations and times of the day. The integration of advanced sensors enables accurate capture of noise variations and patterns, providing detailed information to better understand the dynamics of noise pollution in a specific area.¹³

This section explores the application of web-based systems in relation to noise pollution, highlighting their potential to generate real-time information and promote more effective management actions.

Web-based systems, thanks to their ability to perform continuous, real-time monitoring of noise levels in specific areas, have become an invaluable tool in the fight against noise pollution.¹⁴ These systems make use of a network of strategically connected sensors to collect accurate and up-to-date data on noise pollution at various locations in the city. The availability of real-time information provides the possibility of a rapid and effective response to emergency situations, which can minimise the negative impacts of noise on people’s health and the environment.¹⁵ But their role goes beyond simple monitoring, as web-based systems also provide interactive platforms that play a key role in public awareness and education about noise pollution. These platforms provide data, analysis and useful tips to reduce noise exposure and improve citizens’ quality of life. By making this information available to the community, they promote awareness of the importance of protecting oneself from excessive noise and encourage greater citizen participation in noise pollution management.¹¹ In emergency situations or unexpected events that may significantly increase noise levels, the real-time responsiveness of web-based systems becomes essential. By providing up-to-date information on noise levels in real time, authorities can make quick and coordinated decisions to minimise the detrimental effects of noise on people’s health and the natural environment. This agile response can make a big difference in the protection and safety of the community in critical situations.¹⁶

Method

A laptop Intel Core i5-1135G7 (up to 4.2 GHz with Intel Turbo Boost Technology, 8 MB L3 cache and 4 cores) PCIe NVMe 256 GB solid state processor and 8 GB DDR4-3200 MHz RAM were used, and the agile RUP methodology was used, taking into account its 4 phases.

In the identification of the monitoring stations, an urban map was used to strategically locate the sampling points within the city, especially considering the areas with the highest incidence of vehicular traffic during trafficable hours. This selection was based on the need to capture representative data on noise pollution generated by vehicular traffic.

For the collection of aquatic data, a high quality sound level metre, the Casella model CEL-63x, was used, which allowed precise measurements to be taken in the places chosen as having the highest incidence of vehicular traffic. It is important to note that the device used was previously calibrated and certified by an accredited laboratory, following the guidelines established by the ISO/IEC 17025 standard.

In the field of noise data collection, High Fidelity Sound Sensors and Sound Pressure Level Sensors were implemented, strategically distributed at various points within Tarapoto, covering a variety of urban environments. Each sensor was subjected to a meticulous calibration process, carried out using controlled sound standards and certified reference equipment. This process ensured the reliability of the data collected by carefully adjusting each sensor, minimising possible deviations and guaranteeing consistent and accurate measurements. Calibration, in accordance with rigorous standards, contributed to the reliability and validity of the results obtained in this environmental monitoring study.

An analysis of the requirements for the development of the system was carried out, with meetings and coordination with the competent areas in order to rescue the relevant information for the project, as seen in Annex 1. The processes were identified from the location of the areas, the collection of data with the sound level meter to the mapping of the contaminated areas, finding the transportation system within the urban ecosystem as a disturbing factor in the state of well-being of the people. However, once the data was collected, the design of the system architecture was carried out according to the guidelines established previously, see Figure 1.

Figure 1.

Business use case diagram.

Once the design and architecture were defined, we proceeded to develop the system using JavaScript programming language, HTML, CSS and other technologies such as DBeaver, JQuery and MySql database manager was used. Subsequently, the system was verified and the appropriate tests were carried out to correct the errors identified and improve the process in collaboration with the institution’s managers, as shown in Figure 2.

Figure 2.

Class diagram.

In order to ensure a clear and detailed understanding of the system developed, a block diagram has been developed in Figure 3 to show the overall architecture of the system. This diagram facilitates the visualisation of how each component interacts with the others, allowing a more intuitive interpretation of the data flow and the operations performed. The operation of the system is based on the collection of noise monitoring data, its processing and subsequent presentation in a user-friendly web interface. This interface not only displays the data in real time, but also allows for retrospective analysis and future projections based on historical trends.

Figure 3.

Block diagram of the operation of the system.

The diagram shows how the user accesses and queries the web interface. The web interface, in turn, requests data via an integration API that collects real-time data from the noise monitoring technology. This raw data is sent for processing and analysis. Once processed, the data is stored in a database and subsequently displayed to the user via the web interface.

An essential feature of our system is its ability to interface with existing noise monitoring technology in Tarapoto. Through standardised APIs and communication protocols, the web-based system integrates seamlessly with the monitoring devices, enabling real-time data transmission without interruption. It is crucial to discuss this interaction in more detail, as it represents a point of convergence between pre-existing technology and the innovations introduced by our system.

Regarding the selection of hardware and software, specific criteria were adopted based on efficiency, scalability and robustness. The hardware was chosen considering its processing, memory and storage capacity, thus ensuring that the system can handle large volumes of data without compromising its performance. On the other hand, software choices were based on compatibility, security and ease of integration. The combination of these strategic choices has resulted in a highly efficient system, capable of delivering accurate and reliable results. It is essential to develop this information so that users and stakeholders understand the reasons behind each choice and how these decisions contribute to the overall success of the project.

Noise pollution measurement software provides a comprehensive solution for assessing and quantifying ambient noise levels. This type of programme, such as the one presented in this research ‘Monitoring-System-Noise-Pollution’,²⁹ uses advanced algorithms and acoustic analysis technology to record and analyse the various sound sources present in a given area.

Results and Discussion

Figures 4 and 5 illustrate the process of accessing the system, highlighting the login stage using a username and password. This authentication is essential to safeguard data security by limiting access to authorised users. In addition to its visual representation, this step emphasises the confidentiality and privacy of information, allowing entry only to those with valid credentials.

Figure 4.

Web system login screen.

Figure 5.

Interactive geographical map of the Tarapoto area, with incidence indicators and coloured zoning according to specific areas of interest.

The depiction of these figures highlights how the web system not only addresses functionality, but also aesthetics and the user experience when interacting with the system. This user-centred design dimension can be instrumental in fostering participation and engagement in urban noise pollution management. The presented concept aligns with the observations of Díaz-Barreto³⁰ who emphasises the importance of an intuitive graphical interface for effective data management. The visual and aesthetic presentation of the web system can influence the way users perceive and engage with information. Attractive and user-friendly visual interfaces can capture users’ attention, encourage their active participation and motivate them to explore and understand the data presented. Incorporating interactive graphs and maps into the platform not only enhances the user experience, but also makes complex information easier to understand. Visualising data in the form of interactive graphs can enable users to identify trends and patterns more quickly, contributing to informed, evidence-based decision-making. In addition, comparison with the Meza Chumbes and Sarmiento Borda²⁵ approach that involves collecting data from the source of the problem via a mobile application is valuable. This highlights the versatility and accessibility of the system, which could be a critical factor in collecting accurate, real-time data.

Figure 6 shows a function of the system where users can report incidents related to noise pollution by registering information from affected areas. This option provides an active and participatory interaction by users, which can enrich the database and improve the community’s perception of pollution management.

Figure 6.

Tarapoto, Peru climate monitoring system interface with detailed data and selection options.

This figure highlights how the collection of data from contaminated areas provides significant time optimisation, as the input of information occurs directly at the site of the occurrence. This approach presents a clear convergence with the findings presented in Barba Carrión and Vásquez Aguirre¹¹ where it highlights how time optimisation in dispatch control monitoring leads to a noticeable increase in productivity. The on-site collection strategy not only optimises time, but also improves the quality of the data collected. By recording information at the point of occurrence, the possibility of errors or distortions due to data transcription is minimised. In addition, this methodology can capture real-time data, which is essential for accurate monitoring of patterns and fluctuations in noise pollution levels. The availability of real-time information allows for a more agile response to critical situations and the possibility to take immediate corrective action. The speed of data acquisition is crucial in noise pollution management, as it can directly influence the ability to implement timely and effective solutions. By eliminating the delays inherent in data entry at remote locations, this on-site collection approach reduces barriers that could limit a rapid response to noise pollution situations.

The generation of reports and incident lists, visible in Figure 7, simplifies the consolidation of data and the creation of detailed reports. This process allows detailed tracking of hotspots and patterns. Community participation broadens the coverage and perception of pollution, providing a more complete picture of the urban problem.

Figure 7.

Table of occurrences recorded with detailed climatic and zonal data.

The table of recorded incidents illustrates various environmental parameters in different regions, with a notable focus on temperature, humidity and wind speed. The data suggest different areas of interest, such as ‘Pueblo joven’, ‘Centro’ and ‘El huayco’, with varying noise level measurements, possibly indicating differences in urban or anthropogenic activities in these areas. These results are comparable to other studies that highlight the influence of various environmental factors such as temperature, humidity and wind speed on noise pollution.³¹ This is because temperature influences how sound waves travel; they travel faster in warmer air. They also mention that humidity can also affect sound propagation because moist air, being less dense than dry air, makes it easier for sound waves to travel.³² On the other hand, wind speed and wind direction can amplify or attenuate noise pollution.³³ Understanding the interaction of these environmental variables is therefore crucial when assessing the actual impact of noise pollution at a specific location.

Figure 8 highlights the visual processing of noise pollution data with bar charts and traffic lights. The bar charts allow comparison of levels between zones, facilitating the identification of problem areas. Traffic lights, based on colours, provide immediate perception of risk by levels, improving public understanding and informed decisions. This visual representation not only provides an instant status of affected areas, but also highlights the potential consequences of prolonged exposure. This effective visualisation methodology aligns with the observations of Ceballos Cogollo and Acevedo Buitrago²² who highlight the impacts of chronic exposure to noise pollution. The incorporation of traffic lights and graphics in data presentation has the potential to clearly communicate noise pollution levels and their associated risks, which can be a powerful tool for public awareness and informed decision making. To the same way, Gonzales Herry and Ayala José Elías³⁴ highlight the importance of taking timely action to address this problem by making use of technology.

Figure 8.

Reporting of contaminated areas through a bar chart.

In Figure 9, it is visualised that the web-based system further deepens the understanding of noise pollution events in different urban areas. This detailed section, which provides a date-based analysis, allows a chronological tracking of events in each specific area. This temporal visualisation plays a key role in providing information on the patterns and fluctuations of noise pollution over time.

Figure 9.

Detailed summary of noise levels and harmful effects in the area by dates.

The results discussed above highlight how the visual representation in Figures 4, 6 and 8 of the web system not only addresses functional aspects, but also user experience and aesthetics in the interaction with the system. This user-centred design dimension becomes a key element in fostering participation and engagement in urban noise pollution management.³⁵ The intuitive graphical interface and the ability to interact with interactive maps can simplify the identification of trends and patterns, which influences informed decision making.^36,37

Efficient management of noise pollution through web-based systems involves not only data collection and analysis, but also consideration of ethical and privacy issues. While the main purpose is to monitor noise levels, it is crucial to ensure that no sensitive data or data that may compromise the privacy of individuals or entities is collected. It is therefore pertinent that any document or proposal that addresses the implementation of such systems includes a detailed section on the security and privacy measures adopted.

On the other hand, the sustainability and success of any monitoring system depends to a large extent on the acceptance and active participation of the community and local authorities. It is essential that collaboration and communication mechanisms are established to enable the integration of these actors in the process. The engagement strategy should be detailed in the document, providing a clear framework on how it is planned to sensitise, train and collaborate with the community and authorities in the adoption and maintenance of the system. In addition, to improve the comprehensiveness of the document, it would be beneficial to include contextual information that may influence the dynamics of noise pollution, such as demographic factors, traffic patterns and urban characteristics specific to the region under study.

In that sense, the figures discussed in this context evidence the importance of user-centred design in web-based noise pollution management systems. In situ collection capability optimises efficiency and decision making. Visual representation through traffic lights and graphics highlights risks and promotes awareness. These strategies align with previous findings and emphasise the importance of technology to effectively address urban noise pollution issues.

Conclusions

Noise pollution in urban areas, such as Tarapoto, has emerged as an environmental and social challenge of growing concern. Excessive noise, mainly caused by vehicular and commercial activities, not only disturbs daily tranquillity, but also has implications for the health and well-being of the population. In this context, the implementation of a web-based system to monitor and manage noise pollution is presented as an innovative and necessary solution.

Our research has shown that this web-based system, specifically designed for Tarapoto, is able to efficiently collect, analyse and present data, facilitating decision making based on accurate and up-to-date information. The system’s ability to generate rapid and detailed reports on noise levels in real time represents a significant advance in the city’s environmental management. Furthermore, by providing a holistic view of the noise landscape, it allows authorities and the community to identify critical areas and act proactively. However, the model is not without its challenges. Its implementation can be complex, requiring specialised technical and human resources. While data collection is emphasised, concerns may arise about the privacy and security of the information collected. In addition, its reliance on advanced technologies could present problems in case of technical failures.

The applicability of the model is broad, being relevant to a variety of urban contexts. It can be adapted to different levels of population density, traffic patterns and geographical characteristics, making it suitable for both densely populated areas and regions that are beginning to face noise pollution problems. However, the research has its limitations. Its focus may have been on specific geographic areas, which could restrict its applicability to other regions. The lack of consistent historical data may limit the model’s ability to predict long-term trends. In addition, while the importance of external factors, such as socio-economic, political or climatic changes, is acknowledged, these may not have been fully considered, which could affect the accuracy of the model. Finally, while the importance of community participation is stressed, achieving effective and sustained collaboration can be a challenge in practice.

Limitations

The applicability of the model is broad, being relevant to a variety of urban contexts. It can be adapted to different levels of population density, traffic patterns and geographical characteristics, making it suitable for both densely populated areas and regions that are beginning to face noise pollution problems. However, the research has its limitations. Its focus may have been on specific geographic areas, which could restrict its applicability to other regions. The lack of consistent historical data may limit the model’s ability to predict long-term trends. In addition, although the importance of external factors, such as socio-economic, political or climatic changes, is recognised, these may not have been fully considered, which could affect the accuracy of the model. Also, the cross-validation processes implemented, inherent limitations in sensor accuracy and measurement variability could introduce some uncertainty in the results. Finally, while the importance of community participation is stressed, achieving effective and sustained collaboration can be challenging in practice.

Recommendations

The implementation and effectiveness of a web-based system to manage noise pollution in Tarapoto requires careful consideration of several key aspects. First, continuous validation of the system is essential. To ensure its functionality and usability, it is imperative to establish a periodic testing protocol. These tests, which should involve real users, both expert and lay, will provide valuable feedback for adjustments and improvements. A comprehensive description of these validation steps, including methodologies and evaluation criteria, will not only strengthen the reliability of the system, but also facilitate its acceptance and adaptation by the community.

Second, given the dynamic nature of the technology, regular maintenance and updating of the system is crucial. To keep up with innovations and ensure its long-term effectiveness, it is advisable to establish a structured maintenance plan. This plan should include systematic software reviews, integration of new functionalities and adaptation to emerging technological changes. A detailed discussion of these plans, addressing timelines, responsibilities and methodologies, will ensure the sustainability and relevance of the system in a constantly evolving technological environment.

Finally, given the potential for success of the system in Tarapoto, scalability and expansion are aspects that should not be overlooked. The design of the system should be modular and flexible, allowing for its adaptation to larger areas or areas with different characteristics. In addition, it is essential to consider the replicability of the system in other regions, adapting its functionalities according to the specific needs of each location. The discussion on scalability should be holistic, addressing technical, logistical and financial aspects to ensure successful implementation in diverse contexts.