Automatic Humidity Monitoring System for Archive Preservation: Integration of Arduino with ISO 11799:2016Standard

Archival preservation has become a crucial global concern in recent years. The International Council on Archives(ICA) reports substantial damage to archives in tropical countries due to uncontrolled humidity(Teygeler et al., 2001). There is an increasing trend of adopting automation systems in archival preservation at the international level to monitor and control environmental conditions such as temperature and humidity. These automation systems are proven to reduce energy requirements compared to traditional preservation methods (De La Paz Diulio et al., 2022).The instability of relative humidity in archival storage places has a serious impact on long-term preservation. Unstable humidity can cause mold on the physical paper and disintegration of archival materials (Barthos, 2005). The risk of losing important information due to physical and chemical degradation and technological obsolescence is a real threat to institutions (Nikta, 2019). Non-compliance with international preservation standards can make archives more vulnerable to damage (Barons et al., 2021). The financial implications of archival damage include substantial restoration and repair costs (VanSnick & Ntanos, 2018).The theoreticalframework of this research is built from several main foundations that are integrated with each other. Undang-Undang Nomor 43 Tahun 2009on Archives provides a formal definition of archives and a legal framework for their management in an institutional context. Hendrawan and Ulum (2017)reinforce this perspective by explaining the vital values of archives that include cultural and historical aspects. ISO 11799:2016provides a comprehensive technical standard for the storage of archival documents, specifically related to relative humidity conditions. The Decree of the Head of the National Archives of the Republic of Indonesia Number 12 Year 2000 (Keputusan Kepala Arsip Nasional Republik Indonesia Nomor 12 Tahun 2000) complements the regulatory framework with technical standards for the physical storage of archives. Preventive preservation theory emphasizes the importance of controlling the storage environment to reduce the risk of damage (Ismail & Affandy, 2018).Previous studies have demonstrated the effectiveness of technology implementation in archival preservation. The implementation of Internet of Things (IoT) technology for environmental monitoring has successfully improved conservation conditions at a more efficient cost, as shown in the case study of the Palazzo Doria-Tursi Museum (Manfriani et al., 2021). The implementation of the international standard ISO 14721:2012proves the importance of a structured framework in archival preservation (Rahmanto & Riasetiawan, 2018). The preservation technology framework through the open archive information system (OAIS) has ensured long-term sustainability of access. The integration of technology-based monitoring systems with traditional preservation practices shows promising results in improving the effectiveness of archival preservation. O’Flaherty (2018)emphasized the importance of adaptability to developments in preservation technology.Although the ISO 11799:2016standard has provided parameters for archival preservation, there is a gap in the implementation of integrated real-time monitoring technology. The current monitoring system is not able to provide immediate data for the effective archive preservation decision-making. This gap is even morerelevant given the importance of preventive action in archival preservation. Systems available in the market have limitations in terms of accessibility and implementation costs. The limitations of current monitoring technologies make it difficult for archivists to make informed and quick decisions.Digital transformation in archival institutions is crucial to maintain the relevance and accessibility of archives in the digital age (Wang et al., 2024). Digitization trends show a strong preference for in-house digital preservation over outsourcing(Ahmad et al., 2023). The development of Artificial Intelligence technology improves efficiency through learning-based categorization and natural language summarization (Liu, 2024). Integration of document digitization software with electronic archive systems using OCR technology improves accuracy and speed of processing (Kurylo & Komova, 2024). This is in line with the need for preservation efficiency, which requires continuous efforts and adaptation to technological developments (Zahara & Salim, 2022).This research aims to develop and evaluate an Arduino-based monitoring system to support the preservation of paper archived according to ISO 11799:2016standard. The developed system offers a more economical and easy-to-implement solution for monitoring archive storage conditions. The contribution of this research includes increasing the efficiency and effectiveness of archive preservation through the automation of the monitoring system. The implementation of Arduino technology is expected to provide a moreaffordable alternative to existing commercial systems. The system also allows archivists to conduct a direct assessment of relative humidity stability which is critical for long-term preservation

This research uses a qualitative approach with a prototyping method that allows interaction between system developers and system users (Pressman & Maxim, 2020). Qualitative research was chosen because it aims to describesystematically, factually, and accurately to a certain population or area regarding various characteristics and certain factors (Yusuf, 2016). The prototyping method is usedin developing prototype information systems so that the products developed are in accordance with the needs of users. In this study, researchers intended to describe the process of designing and realizing a relative humidity stability assessment tool accurately and factually. This approach allows researchers to iterate and refine the prototype based on feedback from users.The focus of this research is on archival preservation practices based on the ISO 11799:2016standard integrated with an Arduino development board. The selection of this focus is based on the need to develop paper-based archival preservation and conservation instruments. The research location was chosen at the Administration and Archives Gallery of the Faculty of Administrative Sciences, Brawijaya University since it is an institution established for the purpose of storing and processing archives. This gallery also serves as a learning facility for archival and museology practicum for library science study program students.Design and implementation process was conducted in early 2024 (January-June 2024).Data collection in this research uses two main methods, namely observation and literature study. Observation is done by going directly to the field to observe the problems that occur systematically. Literature study is done by collecting data and information through various sources of data and information derived from the internet and from previous research. The data collected includes information about information preservation and the use of Arduino development boards.The instrument used consists of hardware and software. The hardware includes Arduino Uno Rev 3development boards, DHT11 sensor, 16x2 LCD, piezo buzzer, and traffic LED module. On the other hand, the software used is Arduino IDE for microcontroller programming and Fritzing for electronic circuit design. The instruments were selected based on the need to develop a prototype relative humidity assessment tool that would be used in archive preservation practice.Data analysis was conducted systematically following the procedures described by Sugiyono (2022), where data obtained from observations and documentation were organized into categories. The analysis process began with data reduction to obtain information and insights from the raw data collected. The data was then presented in writing based on factual cases in the field to understand the phenomena that occurred. The final stage of analysis is drawing conclusions from the results of the analysis and presentation of the data that has been done. This analysis process allows researchers to understand and explain research findings more comprehensively

Arduino Uno Rev 3 was chosen as the main development boardbecause it has 14 digital input and output pins, as well as 6 analogueinput pins that are adequate for the needs of the system (Arduino, 2018). The DHT11 sensoris used as a humidity detection component that can convert changes in temperature and humidity into digital signals that can be read by Arduini. Liquid Crystal Display(LCD)16x2 IIC serves as an interface to display sensors readings in an easy-to-read format. Piezo buzzer and traffic LED modules are integrated as output components that provide visual and audio alerts when significant humidity changes occur.The parts of the Arduino Uno are shown in Figure 1, while the LCD IIC specifications are presented in Table 1.Figure 1.Components of Arduino UNO BoardSource: Badami(2016)/(HackerEarth.com)Table 1.Specifications of Liquid Crystal Display IICAlphanumeric display typeSize 16 characters in 2 linesIIC or inter-integrated circuit interfaceOperating voltage 3.3 volts to 5 voltsCommunication with the microcontroller using the IIC protocolSource: Author’s documentation(2025)Programming Logicand Tool DesignThe system programming logic is designed using two main flowcharts that describe the process of value classification and humidity fluctuation detection. The value classification flowchart refers to the ISO 11799:2016 standard which divides humidity levels into three categories: high (Hi), low (Lo), and right (JR) (International Organization for Standardization, 2016). The system is designed to capture humidity data once every 4 seconds to detect changes that occur. The discrepancyprocess between the first and second data is used to calculate the level of humidity fluctuation. The calculation results are then classified into three different categories, each with corresponding visual and audio indicators. Figure 2shows the flowchart of relative humidity categorization based on ISO 11799:2016 variables. The flowchart starts with the recording of relative humidity data from the DHT11 sensor. In addition to the data being categorized by the program to present relative humidity information, the data is also categorized by the ISO 11799:2016 standard and displayed on the LCD. If the data result is at first threshold, which is more than 50%, the program will display the text “HI” or high, which means that the relative humidity level is too high in the room. If the data result is at the second threshold, which is less than 30%, the program will display the text “LO” or low, which means the relative humidity level is too low in the room. If the data result is in the third threshold, which spans 30% to 50%, the program will display the text “JR” or just right, which means the relative humidity level is right in the room. Figure 3. Relative Humidity Fluctuation Detection FlowchartSource: Author’sdocumentation(2025)The flowchartof the intensity categorization of the relative humidity fluctuation level is shown in Figure 3. The diagram starts with the recording of relative humidity data from DHT11 sensor. There are two data recorded by the program, the first relative humidity data and the second relative humidity datawhere the second relative humidity data is recorded 4 seconds after the first relative humidity data. This enables the program to make a discrepancybetween the first and second data while presenting thenumber on the LCD display and visualizing the intensity according to the category. If the result of the difference data is in the first threshold, which spans 0% to 2% or 0% to -2%, the green LED on the device will light up. If the result of the difference data is in the second threshold, which is 3% to 5% or -3% to -5%, the green and yellow LEDs on the device will light up. If the difference data results are in the third threshold, which is more than 5% or less than 5% or less than 5%, the green, yellow, and red LEDs will light up, as well as the buzzer will ring twice.Figure 4.Three-DimensionalRenderingof ToolDesignSource:Author’s documentation(2025)The 3D rendering of an Arduino Uno-based relative humidity measuring device designed according to ISO 11799:2016 standard is show in Figure 4. This device has a block shaped casing and is equipped with mounting brackets in the corners. On the top panel there is a green LCD screen to display data, as well as three indicator LEDs in red, yellow, and green which functioned as a marker of humidity status. On the side of the case are connection ports for power supply and data communication. The design of the tool is compact and functional with ergonomic aspects in mind. Logic Flow and Sensor TestingTable 2.Logic Flow and Sensor TestingDocumentationPictureDescription(a)Low Relative Humidity Fluctuation TestIn evaluatingthe DHT11 sensor and the logic flow of the tool programming, it can be seen in Figure 4a, that the Liquid Crystal Display (LCD) screen that the fluctuation value is showing a value of -0.10. Referring to Figure 3, the amount of value is already located atthe flow of fluctuation threshold, which is -2% up to 0%. At this threshold,the logic flow turns on the green LED, indicating a relatively low level of humidity fluctuation.(b)Moderate Relative Humidity Fluctuation TestSubsequently, in the testing section of the DHT11 sensor and the logic flow of the device programming (Figure 4b), the Liquid Crystal Display (LCD) screen shown that the medium fluctuation value -4.20. in accordance with Figure 3, this value is located at the threshold of moderate fluctuation, which is -5% up to -2%. It was at this threshold that the logic flow turned on the green and yellow LEDs, to signify a moderate level of relative humidity fluctuation.(c)High Relative Humidity Fluctuation TestAs illustrated in Figure 4c, the Liquid Crystal Display (LCD) screen displayed a fluctuation value of 11.20, implying a high degree of variability. Notably, this value exceeds the upper limit of the fluctuation threshold, defined as more than 5%, as depicted in Figure 3. Reaching this threshold prompts the logic flow to activate the green LED, denoting a comparatively modest level of humidity fluctuation.Source: Author’s documentation Systemtests were conducted with a focus on three different levels of relative humidity fluctuation. At low fluctuation levels (0% to±2%),the system displays a green LED indicator to indicate normal conditions. For moderate fluctuations (±2% to±5%),a combination of green and yellow LEDs light up as an early warning. The test results show that the system successfully detects and classifies humidity changes according to predefined parameters. The system is also able to provide appropriate responses inthe form of visual and audio indicators for each level of fluctuation detected.More detailed description ofeach testing wasprovided in Table 2.Analysis of Arduino-based Humidity Monitoring System Implementation for Archive PreservationThis research successfully developed an Arduino-based automatic humidity monitoring system integrated with ISO 11799:2016 standard for archive preservation. The main results show the system coulddetect and classify humidity changes in three categories: low (0% to ±2%), medium (±2%to ±5%), and high (>±5%). The system responds through LED visual indicators and audio alerts corresponding to the level of fluctuation. This achievement addresses the research objective of developing an economical and easy-to-implement monitoring solution.This findings reinforces the research of Manfriani et al. (2021)who demonstrated the effectiveness of IoT implementation in monitoring preservation environments. The developed system supports VanSnick & Ntanos’ (2018)argument regarding the importance ofcost efficiency in archive preservation. However, unlike previous studies that tend to use expensive commercial systems, this research offers a more affordable Arduino-based alternative. In contrast to Liu’s (2024)approach that prioritizes AI-based solutions, this study proves that hardware-based approaches are still relevant and effective for the specific needs of archival preservation.The developed visual and audio notification system provides early warning of changes in humidity, enabling faster preventive action. This supports the findings of De La Paz Diulio et al. (2022)of the efficiency of automation systems in preservation. Despite the strong trend of digital preservation (Wang et al., 2024), this study shows the importance of maintaining a balance between digital and physical preservation.Theoretical implications include the development of a preventive preservation model that integrates technology with international standards. In the practical aspect, the system allows archivists to directly assess moisture stability. The findings have implications for archival preservation policy, particularly regarding the adoption of appropriate technology in preventative preservation.Unexpected results include the consistency of the system’s response to extreme humidity fluctuations, demonstrating the system’s robustness under challenging environmental conditions. This is explained by the robust design of the programming logic and the appropriate selection of components. The prototyping methodology proved effective in system development, but the qualitative approach limits the generalizability of the findings. While this research was successful in developing an effective humidity monitoring system, some limitations need to be acknowledged to provide proper context to the research findings. In terms of methodology, system testing was limited to a single location in the Administration and Archives Gallery of FIA UB and the relatively short duration of testing limited the validation of the system’s reliability in various environmental conditions. The publication of ISO 11799:2024 after the research was completed also created the need to adapt the system to the new standard. Other limitations include the use of a DHT11 sensor with moderate accuracy,limited monitoring range, and lack of integration with long-term data storage systems. Test results that are specific to certain environmental conditions also limit the generalizability of the findings to archival institutions in different geographical locations with different climate characteristics, while the system has not been evaluatedfor different types of archives with varying humidity sensitivity.This research makes a significant contribution to the development of an affordable and effective archive preservation monitoring solution, with practical implications in the form of providing an economical alternative monitoring system that meets the ISO 11799:2016 standard. Theoretically, this research enriches the literature on technology integration in archival preservation and provides a framework for the development of similar systems in other institutions. Future research is recommended to use premiumsensors, conduct long-term testing, and integrate the ISO 11799:2024 standard. The development of a cloud-based system for remote monitoring should also be explored to improve the accessibility of preservation data.Knowledge gaps identified include the need for standardization of humidity monitoring protocols for digital archives and the development of integrated systems that combine humidity monitoring with other preservation parameters. Future research could focus on optimizing the detection algorithm and developing a more user-friendly interface.It is recommended to develop an integrated data storage system with trend analysis capabilities, expand the range of monitoring through the implementation of distributed sensor networks, and integrate with machine learning technology for predictive analysis. Comparative studies with commercial systems and longitudinal evaluation are also needed to validate the cost-effectiveness and sustainability of the system, as well as exploration of integration with digital preservation platforms to support a more comprehensive hybrid preservation approach

By integrating the ISO 11799:2016standard for archival preservation with an Arduino-based automatic humidity monitoring system, this research successfully developed a novel approach to humidity monitoring. The system is capable of detecting and classifying humidity changes in three categories and providing appropriate visual and audio notifications. Notably, the research contributes to the development of a preventive preservation model that integrates technology with international standards and the provision of an alternative monitoring system that is economical and easy to implement. Practical implications include archivists’ direct assessment of moisture stability and guidance for archival preservation policymaking, particularly in the adoption of appropriate technologies. The study’s limitations include testing conducted at a single location, relatively brief test duration, utilization of DHT11 sensors with moderate accuracy, and absence of integration with long-term data storage systems. Future research is recommended to use premium sensors, conduct long-term testing, integrate ISO 11799:2024standards, develop cloud-based systems for remote monitoring, optimize detection algorithms, integrate with machine learning technology for predictive analysis, and conduct comparative studies with commercialsystems to validate the cost-effectiveness and sustainability of the system