Understanding visitor perceptions to guide IoT-based innovations in university ecofarms: insights from Indonesia

This study explores visitor perceptions of UNNES Ecofarm, an integrated farming initiative by Universitas Negeri Semarang, as a foundation for guiding the development of an Internet of Things (IoT)-based automated greenhouse control system. Using a mixed-methods approach, data were collected from 209 participants, including students, educators, and professionals from various sectors. The study first assesses visitor motivations, learning experiences, and perceptions of Ecofarm’s facilities, educational quality, and sustainability practices. Findings reveal that 72% of visitors were primarily motivated by a desire to learn about integrated agriculture, with over 80% expressing positive views on accessibility and sustainability. Based on strong visitor interest in innovation and smart farming technologies, the study proceeded to develop an IoT-driven greenhouse control system to address both environmental efficiency and educational needs. This two-phase approach—first understanding user needs, then developing appropriate technology—demonstrates the importance of grounding innovation in participatory feedback. The research underscores the role of university ecofarms in sustainable development, environmental education, and technological innovation aligned with the Sustainable Development Goals.

1 Introduction

The escalating global challenges of food security and environmental degradation demand innovative, sustainability-focused solutions within agriculture (Athuman, 2023). In this context, agricultural science education plays a critical role in fostering sustainable farming practices, particularly when integrated into the learning experiences of higher education students and university stakeholders. Universities serve as influential hubs for innovation, education, and community engagement (Anthony, 2024; Yamamura and Koth, 2023), making them ideal environments for promoting sustainable farming models that combine crop and livestock production in ecologically balanced systems (Sultan et al., 2024). By embedding integrated farming into curriculum and campus initiatives, universities can cultivate environmental literacy, practical skills, and a sense of responsibility among students, faculty, and staff (Williamson et al., 2023). This holistic exposure supports the development of future agricultural professionals and informed citizens who are capable of advancing sustainable development and resource conservation.

UNNES Ecofarm is a pioneering integrated agriculture initiative developed by Universitas Negeri Semarang in Central Java, Indonesia, designed to promote environmental conservation and sustainable natural resource management within a university environment. Serving as a living laboratory, UNNES Ecofarm actively demonstrates and teaches diverse integrated farming techniques, including hydroponics, aquaponics, organic cultivation, and circular waste management. This program uniquely combines eco-friendly farming practices, such as water- and nutrient-efficient aquaponics systems and closed-loop approaches that recycle waste products—specifically utilizing greenhouse waste and Black Soldier Fly (BSF) larvae frass as natural soil amendments for raised bed organic farming. By managing resources in this synergistic manner, UNNES Ecofarm exemplifies sustainable, integrated farming that minimizes environmental impact while enhancing productivity.

Despite the growing interest in university-based farming (Korir et al., 2022; Maake, 2023; Schrager et al., 2023), limited research has explored how visitor perceptions can directly inform technological development in such settings. Specifically, there is a gap in understanding how public engagement with sustainable agriculture education can guide the creation of contextually relevant innovations to enhance both learning and operational outcomes. This study addresses that gap by first investigating visitor experiences, motivations, and expectations at UNNES Ecofarm through a mixed-methods approach, with the aim of identifying priorities for future development.

The novelty of this research lies in its sequential, user-centered approach: visitor feedback is used not merely as an evaluation tool, but as the foundation for designing an IoT-based automated greenhouse system tailored to the needs and interests identified. While previous studies have tended to separate educational evaluation from technological implementation (Lin, 2022; Ciocan et al., 2024; Ensor and de Bruin, 2022; Odongo et al., 2023), this study integrates the two by using perception data to drive system development. This alignment between stakeholder input and innovation enhances both the practical relevance of the IoT solution and its potential as an educational tool, advancing the role of university ecofarms as responsive, participatory platforms for sustainable development.

In line with this approach, the theoretical foundation of this study draws upon Rogers’ Innovation Diffusion Model (IDM), which explains how new ideas and technologies are communicated and adopted through social systems (Rogers, 2004). This model is particularly relevant for understanding how visitors’ perceptions and learning experiences influence their openness to IoT-based innovations in sustainable agriculture. The five core constructs of the Innovation Diffusion Model (IDM)—relative advantage, compatibility, complexity, trialability, and observability—as outlined by (Dewi et al., 2023), provide a conceptual framework for analyzing visitor responses to the Ecofarm’s technological and educational initiatives. By linking these constructs with participatory user feedback, this study aims to reveal how educational engagement and perceived innovation benefits can accelerate the diffusion of smart-farming practices within university-based ecofarms.

2 Materials and methods

2.1 Integrated farming system

An Integrated Farming System (IFS) is a sustainable and holistic agricultural model that combines crop production, livestock, and resource recycling to optimize land use, improve biodiversity, and support environmental conservation (Bhagat et al., 2024; Singh and Dubey, 2023). It is particularly designed to enhance productivity, profitability, and employment for small and marginal farmers, ultimately ensuring their food and nutrition security and livelihood sustainability (Bahadur et al., 2024; Paramesh et al., 2022). Within higher education institutions, IFS serve as critical living laboratories that not only support sustainable food production but also function as educational platforms fostering environmental literacy and community engagement.

UNNES Ecofarm, launched by Universitas Negeri Semarang in 2024, exemplifies the practical application of integrated farming in a university context. Located on a 3,270 m² site within the campus area, UNNES Ecofarm implements an integrated farming system that synergistically combines various sustainable agricultural practices to promote environmental conservation and resource efficiency. The key activities conducted at the site include:

1. Hydroponic vegetable cultivation, training, and sales

UNNES Ecofarm operates a hydroponic system for vegetable production, providing an efficient soil-less growing environment (Anusree et al., 2024). Various leafy greens and vegetables are cultivated using nutrient-rich water solutions, enabling year-round production with minimal land use and water consumption. Alongside cultivation, training sessions are conducted for students, staff, and visitors to impart practical knowledge of hydroponic techniques. The produce is also marketed locally, supporting both educational outcomes and community engagement.

1. Initiation and education of the aquaponic system

The aquaponic system at UNNES Ecofarm integrates fish farming (Oreochromis niloticus) with hydroponic vegetable cultivation, particularly water spinach (Ipomoea aquatica), in a closed-loop system that exemplifies efficient water and energy use (Chowdhury, 2023). Fish waste provides a natural nutrient source for plants, while nitrifying bacteria convert ammonia into nitrates that serve as organic fertilizer. The plants, in turn, absorb these nutrients and purify the water before it returns to the fish tanks, minimizing water replacement to only compensate for evaporation and achieving up to 90% water savings compared to conventional irrigation. This symbiotic cycle eliminates the need for chemical fertilizers and demonstrates circular nutrient flow within the Water–Energy–Food (WEF) Nexus framework (Yuan et al., 2025). Educational workshops are regularly conducted to help visitors understand nutrient cycling, water conservation, and smart energy use in integrated ecosystem management, reinforcing the Ecofarm’s role as a living laboratory for sustainable agricultural innovation.

1. Utilization of food waste for black soldier fly (BSF) maggot farming

Organic food waste collected from campus cafeterias and other sources is used to rear Black Soldier Fly (BSF) larvae in dedicated composting units. The BSF maggots efficiently convert organic waste into high-protein biomass (Rehman et al., 2023), which serves as sustainable feed for the aquaponic fish. This approach not only reduces organic waste but also creates a circular nutrient flow within the integrated farming system. Educational programs highlight the role of BSF farming in waste reduction and sustainable feed production.

1. Organic raised bed farming using agricultural and maggot rearing waste

UNNES Ecofarm practices organic cultivation in raised beds constructed using agricultural residues from hydroponic systems and frass (insect excrement) from BSF maggot rearing as soil amendments. This method enriches the soil naturally, enhancing fertility and structure without synthetic inputs. The raised bed system improves drainage and accessibility, supporting diverse vegetable and herb cultivation (Gogoi et al., 2022). Through hands-on training, participants learn organic growing principles, soil health management, and the benefits of integrating waste recycling into farming.

In addition to its integrated agricultural components, UNNES Ecofarm also adopts renewable energy solutions through the installation of solar photovoltaic (PV) panels in several strategic areas, particularly at the orchid greenhouse. The solar panels supply clean electricity to operate environmental control systems such as irrigation pumps, exhaust fans, and IoT-based sensors that regulate temperature and humidity. By harnessing solar energy, the Ecofarm significantly reduces dependency on grid electricity and minimizes carbon emissions while maintaining optimal conditions for plant cultivation. The surplus energy generated during daylight hours is stored in batteries to ensure continuous operation at night, supporting both sustainability and energy resilience. Together, these activities demonstrate the principles and advantages of integrated farming, providing a comprehensive, sustainable agricultural model that combines food production, waste recycling, environmental education, and community engagement.

The detail layout of the UNNES Ecofarm can be seen in Figure 1.

Figure 1

Figure 1. UNNES ecofarm layout.

2.2 Demographic information

Table 1 summarizes the demographic characteristics, visit behaviors, and informational backgrounds of the 209 respondents who participated in the survey at UNNES Ecofarm.

Table 1

Table 1. UNNES Ecofarm visitor’s demographic data.

The demographic profile of the respondents reveals several key insights into the UNNES Ecofarm visitor base. A significant majority were female (65%), suggesting that women show greater interest or participation in environmentally focused educational activities. Age distribution was heavily skewed toward younger individuals, with 62% aged 15–24, indicating strong appeal among students and youth, likely due to Ecofarm’s integration with academic programs. Educationally, over half of the respondents (51%) had completed high school or equivalent, while 30% held a bachelor’s degree, reflecting a mixed but largely early-career audience. Consistent with this, students comprised the largest occupational group (50%), though participation from professionals such as lecturers, private employees, and government workers also points to broader relevance across sectors. In terms of visit frequency, most were first-time visitors (68%), suggesting successful outreach to new audiences but also highlighting the potential to improve retention and encourage repeat visits. Information about Ecofarm was primarily obtained through academic channels—university courses (42%) and UNNES staff or lecturers (31%)—indicating a strong institutional role in promotion, while outreach through media and other sources remains limited. Notably, 73% of respondents reported having a personal or professional connection to agriculture, suggesting that the Ecofarm is effectively reaching audiences who are already interested in or aligned with its educational mission.

3 Data collection and data analysis

This study employed a sequential explanatory mixed-methods design combined with a participatory, user-centered technology development approach to explore visitor perceptions of UNNES Ecofarm, a university-based ecofarm initiative at Universitas Negeri Semarang, Indonesia. The mixed-methods design was implemented in two sequential phases: Phase 1 quantitatively examined visitor perceptions to generate insights, while Phase 2 used these findings to guide the design and development of an IoT-based greenhouse control system. This design reflects a user-centered, iterative process in which stakeholder feedback directly informs innovation, consistent with principles of participatory design and best practices in IoT system development.

Phase 1 involved data collection from 209 participants, including students, educators, and professionals from various sectors. Following Cochran’s formula as described by Adhikari (2021), the sample size of 209 respondents corresponds to a population of approximately 457 individuals, assuming a 95% confidence level, a 5% margin of error, and a population proportion (p) of 0.5. This sample size ensured adequate precision and representativeness for analyzing visitor perceptions. Quantitative data were collected using structured questionnaires designed to assess visitor motivations, learning experiences, and perceptions of the Ecofarm’s facilities, educational quality, accessibility, and sustainability practices. The Innovation Diffusion Model (IDM) provided the theoretical framework for interpreting visitor perceptions and their influence on IoT adoption. Specifically, Rogers’ (2004) five key constructs—relative advantage, compatibility, complexity, trialability, and observability—were used as analytical lenses to examine how visitors perceived IoT-based innovation at UNNES Ecofarm. Quantitative data were analyzed using descriptive statistics (means, standard deviations, and frequency distributions) to summarize visitor profiles and perceptions, mean score and standard deviation interpretation to evaluate the level of agreement for each survey item. The analysis was performed using IBM SPSS Statistics 26, and results were presented through frequency tables and percentage distributions. The outcomes of Phase 1 provided a quantitative overview of visitor perceptions that directly informed both the qualitative exploration and the subsequent system design.

Qualitative data were collected through semi-structured interviews and open-ended survey questions to gain deeper insights into visitors’ attitudes, motivations, and needs related to integrated agriculture and sustainable practices. A total of 20 participants were purposively selected from the survey pool to represent diverse visitor backgrounds. The group comprised 12 females and 8 males, aged 19–55 years. Participants included undergraduate students (n = 8), educators and agricultural practitioners (n = 6), community members (n = 4), and IoT developers or technicians (n = 2). This demographic diversity provided balanced perspectives on both the educational and technological dimensions of UNNES Ecofarm. The variation in age, experience, and professional background enriched the qualitative dataset and supported triangulation with the quantitative findings. Qualitative data were analyzed thematically using an inductive–deductive hybrid approach. Open coding was first applied to identify recurring ideas related to learning experiences, innovation, and sustainability. These codes were then organized under predefined categories derived from the Innovation Diffusion Model (e.g., perceived advantage, compatibility). Triangulation was used to integrate findings across methods: patterns emerging from survey data (e.g., strong interest in IoT for farming, high motivation to learn) were compared with qualitative themes to ensure consistency and validation. From this integrated analysis, four overarching themes emerged: (1) Perceived educational advantage (linked to relative advantage); (2) System compatibility with sustainable practices; (3) Ease of use and engagement (reflecting the overlap between complexity and trialability) and (4) Visibility of innovation benefits (related to observability). These constructs and themes collectively informed the IoT system design by aligning technological features—such as dashboard interactivity, automation, and feedback mechanisms—with users’ perceived needs, expectations, and readiness for adoption.

Phase 2 built upon the insights gained from Phase 1 to design and develop an IoT-driven greenhouse control system tailored to the educational and environmental objectives identified in the study. The system integrated sensors for monitoring environmental parameters such as temperature, soil moisture, and humidity, all connected to a microcontroller that enabled real-time monitoring and automated control of greenhouse functions, including irrigation and ventilation. A cloud-based platform (Firebase) facilitated remote access, data storage, and user interaction. The development process followed a participatory design approach, ensuring that user feedback continuously informed system refinement and alignment with visitor interests in innovation and smart-farming technologies.

Validation of findings was conducted through methodological, data source, and participant triangulation. Quantitative and qualitative results were cross-checked for convergent patterns, and a prototype evaluation was carried out in which users interacted directly with the EcoFarm Dashboard. Functionality and user satisfaction were assessed through direct observation and short feedback questionnaires. Participant feedback confirmed the system’s usability, educational relevance, and alignment with user needs. This multilevel validation—combining data triangulation, member checking, and prototype testing—ensured the robustness, reliability, and credibility of both the empirical findings and the design outcomes.

4 Results and discussion

4.1 Visitor’s motivation

The data indicate that educational objectives are the dominant motivation for visiting UNNES Ecofarm. The fact that 72% of visitors came to enhance their understanding of integrated agriculture underscores the Ecofarm’s core strength as a learning site, particularly for those interested in sustainable and holistic farming systems. This is further supported by the 48% who visited out of a general curiosity to learn new things, and 43% who were motivated by academic or institutional tasks, highlighting the site’s strong alignment with formal education purposes.

The interest in learning about specific animals or plants (57%) suggests that visitors are also drawn to tangible, subject-specific content within the Ecofarm, pointing to an opportunity for more targeted or themed exhibits, workshops, or educational signage. Meanwhile, the social motivations—meeting new people (19%), connecting with friends or acquaintances (24%), and spending time with family (14%)—though less dominant, still reflect the Ecofarm’s role as a social and recreational space. These findings indicate the potential for Ecofarm to develop or expand community-based activities and group-friendly programs to strengthen its appeal beyond individual learners. The data visualization can be seen in Figure 2.

Figure 2

Figure 2. Motivations for visiting UNNES Ecofarm.

The findings indicate that UNNES Ecofarm effectively draws visitors mainly through its integrated agriculture education, highlighting the important function of university-based ecofarms as centers for hands-on learning and environmental education. This role corresponds with the wider importance of university-led agricultural extension in driving reform and innovation, similar to the finding of previous research about China’s university-based agricultural extension system (Wang et al., 2020). By fostering cognitive (Asogwa et al., 2016) and affective learning (Ho, 2016), such settings promote environmental literacy (Sherry, 2022) and a sense of stewardship (Kiers and Owens, 2021), which are essential for sustainable development.

Simultaneously, UNNES Ecofarm functions as a secondary social and recreational venue (Harris and Holley, 2016), offering visitors an opportunity to relax, interact, and connect with nature outside of formal educational activities. Literature on green spaces and educational farms highlights that combining educational functions with opportunities for recreation (Petroman et al., 2016) and socializing (Dreby and Carr, 2019) enhances visitor satisfaction, encourages return visits, and broadens community engagement. Social experiences can foster informal learning (Galanis et al., 2016) and peer-to-peer knowledge exchange (Sutherland and Marchand, 2021), complementing structured educational programs.

Balancing these dual dimensions—education and social experience—can thus create a holistic public learning environment that addresses cognitive, social, and emotional needs of visitors. Such integration supports the concept of “edutainment” in environmental education, where learning is both informative and enjoyable, increasing motivation and engagement (Mulianingsih et al., 2025). This balance aligns with calls in sustainable development literature to design multifunctional green spaces that maximize educational impact while promoting wellbeing and community cohesion (Edeigba et al., 2024).

4.2 Facility and program evaluation

Table 2 summarizes the descriptive statistics for each survey item, including the question, mean scores, standard deviations (SD), and a brief interpretation of the respondents’ feedback regarding UNNES Ecofarm.

Table 2

Table 2. Visitor feedback on UNNES Ecofarm.

The survey results from UNNES Ecofarm reveal a predominantly positive visitor perception of the farm’s facilities, educational programs, and activities, with mean scores exceeding 4.0 across measured items. This indicates a strong level of satisfaction and agreement regarding the adequacy of physical infrastructure, the clarity and effectiveness of the integrated agricultural education offered, and the environmental sustainability of farm management practices. These findings resonate with previous research emphasizing that well-maintained facilities (Jabar et al., 2024) and genuine educational content (Do and Nguyen, 2025) are fundamental to positive visitor experiences in agricultural education centers. Moreover, visitors’ recognition of the educational value and interest generated by farm activities aligns with literature suggesting that engaging, hands-on learning opportunities are critical for fostering environmental awareness and stewardship (Brahma, 2025).

However, the data also pinpoint essential areas for enhancement, reflective of emerging trends in ecofarm and agro-tourism development. Strong visitor support for increased promotional efforts underscores the challenge of public outreach commonly noted in similar settings, where awareness often limits broader community engagement (Rogers, 2011; Umar, 2025). Additionally, the call for more diverse and interactive educational programs aligns with contemporary educational theory advocating for varied pedagogical approaches, including experiential, participatory, and technology-enhanced learning, which are shown to deepen visitor engagement and knowledge retention (Zenios, 2020). The high endorsement for involving communities and students in ecofarm development also parallels studies highlighting the benefits of participatory governance and co-creation models in sustainable agriculture education, which can enhance relevance, ownership, and impact (Pretty et al., 2005).

While visitor safety and comfort are generally well-rated, the relatively lower scores and higher variability suggest that further attention is necessary. This echoes similar findings in environmental education venues where perceived safety and accessibility critically influence visitor satisfaction and return rates (Jarvis et al., 2016). Addressing these concerns through infrastructure improvements and inclusive design can bolster the overall visitor experience. Taken together, these insights present a balanced perspective that both validates existing strengths at UNNES Ecofarm and identifies actionable opportunities for strategic development. This dual focus is consistent with best practices in sustainable educational farm management, which emphasize continuous improvement through stakeholder feedback to align with evolving educational, social, and environmental goals.

4.3 Development suggestion

To prioritize development initiatives at UNNES Ecofarm, 209 visitor responses were analyzed based on their top three recommended options. Each recommendation was evaluated according to its position in the respondent’s list of priorities: (1) 1st priority was given a weight of 3 points; (2) 2nd priority received 2 points; (3) 3rd priority received 1 point. Applying this weighted scoring system will obtain a more meaningful understanding of what matters most to visitors, not just by frequency, but by the strength of preference. Eight specific development options were considered, ranging from technological integration (e.g., IoT) to infrastructure and educational enhancements. The detail of visitor’s development suggestion for UNNES Ecofarm can be analyzed in Table 3.

Table 3

Table 3. Weighted ranking of ecofarm development options.

The results show that the highest development priority identified by visitors is the implementation of IoT for farming activities, selected as the top choice by 99 respondents. This highlights a clear expectation for modernization and the application of smart technologies in agricultural management. The strong demand for interactive education facilities and IoT-based learning also reflects visitors’ preference for experiential and technology-enhanced learning environments. These findings indicate that the Ecofarm’s visitors are not only interested in sustainability practices but also in the integration of digital innovation that enhances both productivity and learning engagement. It emphasizes on technological innovation is consistent with findings from other university-based agricultural initiatives. The emphasis on technological innovation aligns with the findings of Tariq et al. (2024), who reported that the implementation of IoT-based systems in education has significantly improved safety, operational efficiency, and student comprehension through more interactive and immersive learning experiences. The emphasis on technological innovation aligns with the findings of Tariq et al. (2024), who reported that the implementation of IoT-based systems in education has significantly improved safety, operational efficiency, and student comprehension through more interactive and immersive learning experiences. Moreover, their study highlights how IoT integration in educational administration promotes digital transformation and streamlines management processes, reinforcing the broader value of IoT adoption across educational and institutional contexts. Similarly, Karunathilake et al. (2023) emphasized that precision agriculture driven by IoT and advanced technologies plays a vital role in enhancing productivity, minimizing environmental impacts, and empowering farmers through education and infrastructure development.

The relatively lower ranking of infrastructure and marketing improvements suggests that visitors perceive these as supportive but not transformative elements of development. This differs from the findings of Jabar et al. (2024) in botanical garden visitor studies, where comfort and facilities were top priorities. The contrast may stem from the Ecofarm’s unique educational focus—where learning and innovation take precedence over leisure amenities. Nonetheless, the high cumulative scores for training/workshops and community/student involvement reflect recognition that human capacity building and participatory governance remain essential for sustaining technological systems. Previous studies also affirm that the long-term success of educational ecofarms depends not only on technology adoption but on continuous skill development and community participation (Kumar et al., 2025; Prajapati et al., 2025).

The results reveal a coherent developmental direction: visitors envision UNNES Ecofarm as a hub for smart, participatory, and sustainability-oriented agricultural education. Future development strategies should therefore balance digital innovation with capacity-building programs to ensure accessibility and equitable participation. Establishing modular training in IoT operation, energy management (solar PV systems), and aquaponic maintenance can strengthen both the technological and human dimensions of sustainability. This dual focus—on innovation and inclusion—resonates with international best practices in sustainable university farming (Dai et al., 2024), supporting the Ecofarm’s role as a living laboratory for achieving the Sustainable Development Goals.

4.4 Design and implementation of IoT for smart farming system

A smart farming system based on the IoT specifically designed to automatically regulate temperature and detect harvest readiness for mustard greens (Brassica juncea). The implementation consists of three main subsystems, each contributing to the automation and remote monitoring capabilities of the system.

1. IoT-based environmental control and monitoring system

The first subsystem is an automated temperature control system, which utilizes a DHT22 temperature and humidity sensor in conjunction with an ESP32 microcontroller. This configuration enables automatic activation and deactivation of an exhaust fan based on predefined temperature thresholds. When the ambient temperature reaches or exceeds the set threshold (e.g., 30 °C), the ESP32 sends a control signal to a relay, which in turn activates a magnetic contactor. This contactor connects the 220 V power supply to the exhaust fan, thereby initiating cooling. Conversely, when the temperature drops below the threshold, the relay is deactivated, and the system turns off the fan. This automated control loop ensures a stable microclimate within the greenhouse.

This system is connected to a web-based dashboard, allowing users to monitor environmental parameters and fan status remotely. Real-time data regarding temperature and humidity are transmitted to the server via WiFi, and can be accessed through an online platform, thereby enabling continuous monitoring from any location. The control system functions as follows:

a. The ESP32 initializes a connection with the DHT22 sensor, configuring it to read environmental data.

b. Temperature (and optionally humidity) values are periodically read and stored for control logic processing.

c. Based on the control logic:

• If temperature ≥ 32 °C → ESP32 activates relay → contactor ON → fan turns ON.

• If temperature ≤ 30 °C → relay is deactivated → contactor OFF → fan turns OFF.

d. The relay acts as an interface between the low-voltage control circuit and the high-voltage actuator (fan).

e. The magnetic contactor activates only when current flows through coil terminals.

f. The exhaust fan, connected to the contactor’s terminals, is powered only when the contactor is active.

g. Sensor data (e.g., temperature) are transmitted to the server via WiFi for logging and visualization.

h. Fan status and environmental readings are displayed via a serial monitor (during debugging) or an IoT-integrated dashboard.

This control mechanism was deployed in designated zones within the greenhouse, as shown in the physical layout diagrams, ensuring optimal placement of sensors and exhaust units for effective environmental regulation.

Figure 3–5 illustrate the applications of IoT technology in the greenhouse system, specifically through the installation of exhaust fans for automatic temperature control. The exhaust fan system can be integrated with a mobile phone temperature monitoring application using IoT technology. Temperature sensors continuously measure indoor temperature and transmit the data to a microcontroller equipped with Wi-Fi connectivity. The microcontroller sends the temperature readings to a cloud-based platform, which communicates with a mobile application that displays real-time temperature data and system status. When the detected temperature exceeds a predefined threshold, the microcontroller automatically activates the exhaust fans via a relay module to expel hot air and maintain thermal stability. Conversely, when the temperature falls within the desired range, the exhaust fans are deactivated. This system enables remote monitoring and automated control, improving energy efficiency, indoor air quality, and operational convenience.

1. Wireless sensor network (WSN)

Figure 3

Figure 3. The ecofarm greenhouse.

Figure 4

Figure 4. Blower or intake fan.

Figure 5

Figure 5. Exhaust fan.

The second subsystem involves a Wireless Sensor Network (WSN), a decentralized communication model wherein multiple sensor nodes are distributed throughout the greenhouse to collect and transmit environmental data. Each node is equipped with a DHT22 sensor, an ESP32 microcontroller, and a WiFi communication module. The network adopts a star topology, where each sensor node acts as a client transmitting data directly to a central server (sink node) without inter-node communication.

The key features of the WSN implementation include:

a. Periodic measurement of temperature and humidity by each node.

b. Data transmission to the central server using protocols such as HTTP POST over WiFi.

c. Real-time logging, storage, and visualization of environmental data.

d. Direct node-to-server communication, enhancing simplicity and reliability.

e. Transmission of metadata including node ID, signal strength, relay status, and timestamps.

This subsystem allows for real-time, remote monitoring and contributes to the overall transparency and efficiency of the integrated farming environment.

1. Web and android-based monitoring platforms

The third subsystem comprises the EcoFarm Dashboard, a cloud-integrated monitoring and control interface available via both web and Android applications. The system is built upon Firebase for real-time data synchronization between IoT devices (sensor nodes) and the monitoring dashboard as can be seen in Figure 6.

Figure 6

Figure 6. IoT for monitoring intake fan remotely.

The dashboard provides the following functionalities:

a. Real-time data visualization: Environmental data (temperature and humidity) are displayed as dynamic graphs, allowing users to track microclimatic changes over time.

b. Live data updates: Data is pulled directly from Firebase and updated in real-time without the need for page refreshes, enhancing usability and responsiveness.

c. Remote control and diagnostics: The platform enables users to monitor fan operation status and environmental trends remotely, thereby supporting timely decision-making and operational efficiency in greenhouse management.

Collectively, these subsystems establish a robust IoT-based integrated farming framework capable of supporting both precision agriculture and agricultural education initiatives, aligning with the goals of sustainability, automation, and user accessibility.

To facilitate user interaction and remote monitoring, the system is equipped with a dedicated web and Android application, collectively referred to as the “EcoFarm Dashboard.” This IoT-based platform enables real-time monitoring and control of environmental conditions, specifically designed to support agricultural operations within the greenhouse environment. The design of the Ecofarm monitoring web interface can be observed in Figure 7 and the Android application interface is shown in Figure 8.

Figure 7

Figure 7. Ecofarm Dashboard web interface.

Figure 8

Figure 8. EcoFarm Dashboard android interface.

The EcoFarm Dashboard operates using Firebase as its backend infrastructure, which ensures seamless data synchronization from the field-deployed nodes to the user interface. Both the web and mobile applications present users with live visualizations of temperature and humidity data through dynamic, real-time graphs. These charts are automatically updated with each new data transmission from the IoT devices, eliminating the need for manual page refreshes and enhancing user responsiveness. Additionally, the system displays the operational status of key actuators, such as the exhaust fan, enabling users to monitor and assess the effectiveness of environmental controls from any location with internet access.

The EcoFarm Dashboard serves as an intuitive, web- and Android-based interface designed to provide real-time environmental data monitoring and control capabilities for the IoT-driven greenhouse system developed at UNNES Ecofarm. This dashboard aggregates sensor data such as temperature, soil moisture, and humidity, presenting it through user-friendly visualizations and alerts. By enabling remote access via mobile and web platforms, the dashboard empowers educators, students, and other stakeholders to actively engage with the greenhouse environment, facilitating hands-on learning, timely decision-making, and efficient management of agricultural conditions.

Beyond monitoring, the dashboard supports automation features that can trigger irrigation, ventilation, or shading systems based on preset thresholds, thereby optimizing crop growth conditions while conserving resources like water and energy. The interactive nature of the dashboard aligns with visitor interests in innovation and smart farming technologies, as revealed in the study’s findings. It transforms passive observation into participatory experience, reinforcing the educational goals of the Ecofarm by demonstrating how IoT technologies can be effectively integrated into sustainable agriculture practices.

This digital interface also supports the broader objectives of the university ecofarm by promoting environmental education that is accessible, transparent, and responsive to user feedback. Through continuous data collection and system responsiveness, the dashboard fosters a dynamic learning environment that adapts to evolving user needs and agricultural challenges. Consequently, it exemplifies how visitor perceptions and technological innovation can be synergistically harnessed to advance sustainable development goals within a university setting.

The two-phase, participatory approach employed in this study—specifically, the visitor assessment process for developing a prototype IoT greenhouse—aligns with established best practices for promoting agricultural technology adoption. User involvement enhances perceived compatibility and observability, two constructs from Rogers’ diffusion theory that are strongly correlated with higher adoption rates (Overbye-Thompson and Hamilton, 2025). Comparable reviews at both the Indonesian and regional levels identify similar facilitating factors such as perceived relative advantage and demonstrability, while also emphasizing persistent barriers including connectivity constraints, limited maintenance capacity, and low levels of digital literacy. These are factors that the Phase 2 prototype has not yet examined longitudinally. Situating the IoT findings within this broader body of evidence would substantially strengthen the manuscript. For instance, the discussion could outline specific mitigation strategies such as structured training modules, the designation of local maintenance “champions,” and the incorporation of offline fallback modes that parallel recommendations frequently cited in the literature.

4.5 Theoretical and practical implications

This study advances the application of the Innovation Diffusion Model (Rogers, 2004) within the emerging field of sustainability education and smart agriculture. By situating the model in an educational ecofarm context, the research highlights how learning motivation, perceived educational value, and openness to innovation collectively shape individuals’ readiness to adopt new technologies. The findings demonstrate that visitors’ perceptions of usefulness and relevance are not only influenced by the perceived advantages of technology but are also deeply embedded in the experiential and participatory nature of their learning environments. This insight broadens the traditional interpretation of diffusion theory—typically focused on commercial or industrial adoption—by showing that educational engagement can serve as a catalyst for technological diffusion. Furthermore, the integration of user-centered design principles with the theoretical constructs of the Innovation Diffusion Model provides a novel analytical lens for examining how stakeholder participation, feedback loops, and experiential learning can accelerate the acceptance and institutionalization of technology-driven sustainability innovations. Thus, this study contributes to both innovation adoption theory and educational technology literature, emphasizing the dynamic interplay between human learning processes and technological change.

From a practical standpoint, the study offers valuable insights for universities, policymakers, and agricultural practitioners seeking to integrate IoT-based systems into sustainability programs. The participatory development process implemented at UNNES Ecofarm demonstrates a feasible and replicable approach for other educational institutions aiming to merge environmental education with smart farming technologies. Through active stakeholder involvement, the project ensured that system design decisions were grounded in real user needs, thereby increasing both the relevance and sustainability of technological interventions. The IoT-based greenhouse prototype developed in this study exemplifies how digital innovations can improve environmental efficiency while simultaneously enhancing experiential learning opportunities for students and visitors. This dual focus on ecological performance and educational impact supports broader global objectives, particularly the Sustainable Development Goals (SDG 4: Quality Education and SDG 12: Responsible Consumption and Production). Beyond the university setting, the study’s participatory approach can inform policy frameworks that encourage co-creation and technological inclusivity in agricultural innovation, reinforcing the role of higher education as a key driver of sustainable, technology-enabled transformation.

5 Conclusion

The study on visitor perceptions at UNNES Ecofarm highlights the critical role of understanding user needs in guiding IoT-based innovations within university ecofarms. Findings demonstrate strong visitor interest in integrated agriculture, sustainability, and smart farming technologies, which provided a clear foundation for developing an IoT-driven automated greenhouse control system tailored to both educational and environmental objectives. By combining a mixed-methods assessment of visitor motivations and experiences with a participatory design approach, the research successfully aligned technological development with stakeholder insights, thereby enhancing the practical relevance and educational value of the innovation. This user-centered and iterative methodology underscores the potential of university ecofarms to serve as dynamic platforms for advancing sustainable development, environmental education, and technological innovation in line with global sustainability goals.

However, this study has limitations that warrant consideration. The participant sample, while diverse, was skewed toward younger visitors and students closely affiliated with the university, which may limit the generalizability of findings to broader public audiences or other regional contexts. Additionally, the IoT system development focused primarily on environmental monitoring and automation functions without extensive long-term evaluation of system performance or user engagement post-implementation. Technical challenges such as sensor calibration, network reliability, and scalability were also beyond the scope of this initial phase. Future research should seek to address these limitations by expanding participant demographics to include more diverse community members and stakeholders. Longitudinal studies examining user interaction with the IoT system over time would provide valuable insights into its educational impact and operational effectiveness. Moreover, integrating advanced technologies such as artificial intelligence for predictive analytics, expanding sensor capabilities, and improving system interoperability could further enhance smart farming applications. Finally, exploring participatory approaches to involve students and local communities actively in the maintenance and evolution of such technologies could strengthen the role of university ecofarms as collaborative innovation hubs for sustainable agriculture and environmental stewardship.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

NM: Conceptualization, Data curation, Investigation, Resources, Supervision, Writing – original draft, Writing – review & editing. IM: Data curation, Methodology, Writing – original draft, Writing – review & editing. SS: Formal analysis, Project administration, Validation, Writing – original draft, Writing – review & editing. AF: Formal analysis, Project administration, Validation, Writing – original draft, Writing – review & editing. LD: Data curation, Formal analysis, Writing – original draft, Writing – review & editing. CD: Project administration, Resources, Validation, Writing – original draft, Writing – review & editing. HZ: Formal analysis, Project administration, Resources, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This research was funded by the Research and Community Service Institute of Universitas Negeri Semarang under the Riset Kolaborasi Indonesia PTNBH scheme, with the project titled “Innovation Diffusion Model of the Internet of Things in Smart Farming within the Digital Village Program to Achieve a Sustainable Green Economy.” The funding was granted based on Decree Number B/393/UN37/HK.02/2025 dated April 21, 2025, and Research Contract Number 13.25.4/UN37/PPK.11/2025.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that Gen AI was used in the creation of this manuscript. Generative AI was used English sentence improvement in grammar and coherence.

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