INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1701
www.rsisinternational.org
Community Environmental Health Monitoring: Solar-Powered IoT
Air Quality Assessment for Public Health Decision-Making
Salleh
1
, N. R. Mohamad
1
, N. M. Z. Hashim
1
, M. H. Misran
1
, N. A. Shaharuddin
2
1
Center for Telecommunication and Innovation (CeTRI), Fakulti Teknologi dan Kejuruteraan
Elektronik dan Komputer (FTKEK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya,
76100, Durian Tunggal, Melaka, Malaysia
2
Faculty of Hotel and Tourism Management, Universiti Teknologi MARA, Melaka, Malaysia
DOI:
https://dx.doi.org/10.47772/IJRISS.2025.910000144
Received: 06 October 2025; Accepted: 14 October 2025; Published: 06 November 2025
ABSTRACT
Environmental health disparities notably affect communities that lack access to real-time air quality data, which
is crucial for making informed public health decisions. This study develops and evaluates a solar-powered IoT
environmental health monitoring system to address environmental health information inequities through
sustainable, community-centered implementation. Temperature-humidity sensor, barometric pressure sensor,
gas sensor, and optical dust sensor are integrated with ESP32 microcontroller and Things Board IoT platform,
powered by solar panels, for energy autonomy. Mobile interface provide community members with real-time
environmental data and local air quality information. Field deployment in Malacca, Malaysia, showed successful
continuous operation with a highly cost-effective system that saved money compared to commercial alternatives
and had zero operational electricity expenses due to solar autonomy. Results showed large multi-dimensional
outcomes, including increased community environmental health awareness, social cohesion supporting
collaborative action, and strong connection with six Sustainable Development Goals (SDG). The implementation
greatly improved community access to real-time air quality data, addressing environmental health inequities and
laying the groundwork for community-based activism. Environmental sustainability assessment found little
ecological footprint with renewable energy operation supporting climate mitigation through fossil fuel
displacement and adaptation through community monitoring capability. This study offers a reproducible,
economically viable paradigm for technical innovation, community empowerment, environmental preservation,
and sustainable development. The findings affect environmental health policy, community-based surveillance
expansion, and environmental justice through accessible monitoring technology.
Keywords: Community environmental health monitoring; Solar-powered IoT systems; Environmental health
equity; Sustainable development goals; Community empowerment
INTRODUCTION
Increasing apprehensions regarding environmental health and air quality have sparked considerable interest in
the creation of innovative community-based monitoring strategies for public health purposes. The Internet of
Things (IoT) has emerged as a pivotal platform for the real-time collecting of environmental data, crucial for
efficient community health monitoring and environmental health decision-making. With the rapid acceleration
of urbanization, especially in developing countries, conventional environmental monitoring methods are proving
insufficient for facilitating community-level public health initiatives; thus, the incorporation of IoT technologies
presents opportunities to augment environmental health monitoring and enhance the transparency of
environmental health data for communities (Jo et al., 2020; Peixe & Marques, 2024).
The integration of solar electricity with IoT devices improves their utility for monitoring community
environmental health, particularly in remote or underserved regions where traditional power infrastructure
restricts environmental health surveillance capabilities (Saravanakumar et al., 2024). The worldwide transition
to renewable energy sources corresponds with modern sustainability objectives and promotes environmental
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1702
www.rsisinternational.org
health equity. Solar-powered IoT systems for community air quality monitoring deliver vital environmental
health information while fostering the adoption of renewable energy within the community. Moreover, as
communities endeavor to alleviate the detrimental health impacts of pollution, utilizing technology for
environmental health monitoring holds considerable ramifications for health awareness, community
involvement, and the formulation of public health policies (Li et al., 2024; Dosymbetova et al., 2023).
Notwithstanding substantial progress in environmental monitoring technologies, important hurdles persist in the
implementation of community environmental health. Conventional air quality monitoring systems demonstrate
deficiencies in regional coverage, temporal resolution, and energy efficiency, leading to delayed or insufficient
environmental health data for community decision-making (Múnera et al., 2021). The absence of thorough,
prompt environmental health data obstructs efficient public health responses to pollution incidents and persistent
air quality deterioration at the community level. Traditional monitoring methods generally concentrate on
particular contaminants, neglecting real-time, holistic community health evaluations and failing to account for
critical environmental health interactions impacting local communities.
To tackle these difficulties, it is essential to implement solar-powered IoT environmental health monitoring
devices that function autonomously and provide real-time updates and alarms regarding air quality conditions
pertinent to community health. These systems must track many environmental health factors and operate
consistently in diverse settings, ensuring continuous functionality independent of traditional power infrastructure
(Ng & Dahari, 2020). This research seeks to provide a scalable and efficient method that improves community
knowledge of environmental health, fosters environmental health literacy, and builds responsive frameworks for
addressing air quality issues at the community level.
LITERATURE REVIEW
Recent studies on IoT-based environmental monitoring systems reveal increasing potential in community health
settings. Jo et al. demonstrated that IoT technologies may efficiently monitor particulate matter in urban settings,
underscoring the practicality of integrating these systems with community health infrastructure (Jo et al., 2020).
Research on smart environmental monitoring systems utilizing Low Power Wide Area Network (LPWAN)
technologies reveals considerable potential for economical transmission of environmental health data across
extensive regions, appropriate for community-wide implementations (Shashank et al., 2022; Peixe & Marques,
2024). Li et al. highlight the necessity of including renewable energy sources into IoT frameworks to guarantee
that environmental health monitoring is sustainable and consistent with community sustainability objectives
(Saravanakumar et al., 2024).
Practical applications in smart cities illustrate the ability of these systems to enhance community health outcomes
via real-time environmental data gathering and community engagement in environmental health programs (Li et
al., 2024; Dosymbetova et al., 2023). The integration of community health objectives underscores the social
ramifications of technology advancements, wherein transparency in environmental health data and community
involvement can significantly alleviate the detrimental health effects of air pollution.
Despite the growing use of IoT-enhanced environmental monitoring for health purposes, significant research
deficiencies persist in thoroughly investigating the complete spectrum of environmental health and social
ramifications of solar-powered community monitoring systems. A notable disparity pertains to the scalability
and practical application of these technologies in various urban and rural community health settings. Numerous
research have concentrated predominantly on technical advancement and functioning, overlooking community
integration and the long-term effects on public health outcomes (Jahandar et al., 2021).
Research on system optimization for various geographical and socio-economic community health contexts is
inadequate, prompting inquiries regarding adaption and efficacy across different demographic groups.
Contemporary literature frequently lacks thorough frameworks that encompass both the technical dimensions of
solar-powered IoT monitoring systems and their potential to bolster community resilience against environmental
health hazards. The potential of these systems as instruments for environmental health education and policy
advocacy is an inadequately researched domain, especially in communities where awareness of environmental
health and access to environmental data can impact collective health decisions (Lin et al., 2022).
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1703
www.rsisinternational.org
This study tackles these deficiencies by creating and assessing a solar-powered IoT environmental health
monitoring system tailored for community deployment and public health decision-making assistance. The
project seeks to illustrate the technical viability of ongoing, community-centered environmental health
monitoring while creating a solid platform that can function as an intervention tool for forthcoming public health
studies on environmental health awareness and behavioral modification. This study enhances environmental
health literature by systematically developing, implementing, and validating a cost-effective community
monitoring system, while advancing the comprehension of how accessible environmental health data can
empower communities and promote equity in environmental health.
The study offers a replicable framework for merging technological innovation with public health outcomes,
delivering practical insights for the implementation of analogous systems in various community contexts, while
laying the groundwork for interdisciplinary research that investigates the connections between access to
environmental health information and community health behaviors.
METHODOLOGY
This study utilized a mixed-methods research methodology that integrated technical system development with
social science evaluation techniques to investigate the community impacts of environmental health monitoring
technology. The methodology combined engineering design concepts with community-based participatory
research, highlighting technical validation and social effect evaluation. The research design employed a
sequential explanatory methodology, commencing with prototype development and technical validation,
subsequently progressing to community deployment and the social evaluation of environmental health awareness
and community empowerment outcomes.
The study employed a socio-technical systems framework, acknowledging that environmental health monitoring
systems operate within intricate social contexts where technology adoption, community involvement, and health
behavior modification converge. The theoretical framework utilized environmental justice theory and
community empowerment models to analyze how access to environmental health information might mitigate
health inequities and enhance community agency in environmental health decision-making. The study was
carried out in Malacca, Malaysia, in a residential area marked by varied socio-economic backgrounds and
experiences with environmental health issues such as urban pollution and intermittent haze occurrences. This
site was chosen through purposive sampling to represent populations facing environmental health inequities,
while possessing adequate infrastructure to facilitate IoT adoption for community health applications.
Technical Advancement and System Architecture
The technological aspect entailed the methodical creation of a solar-powered IoT air quality monitoring system
intended for community accessibility and public health purposes as shown in Figure 1. The system incorporated
hardware elements such as the ESP32-WROOM-32 microcontroller for energy-efficient processing and
community Wi-Fi connectivity, the MQ-135 gas sensor for detecting CO₂, NH₃, and NOₓ gases pertinent to
public health, environmental sensors (AHT20 temperature-humidity sensor, BMP280 barometric pressure
sensor), and the GP2Y1014AU0F optical dust sensor for assessing particulate matter crucial for respiratory
health evaluation. The solar power subsystem consisted of a 20W monocrystalline solar panel, an MPPT charge
controller, and a 12V 7Ah sealed lead-acid battery to facilitate autonomous operation for ongoing community
environmental health monitoring. A user interface featured a 16x2 I2C LCD display and status LEDs enabling
prompt community access to environmental health data. Custom firmware was created with Arduino IDE,
enabling real-time data transmission and viewing via the ThingsBoard IoT platform, which offers user-friendly
web and mobile interfaces tailored for a varied community audience. Figure 2 show the flowchart of system.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1704
www.rsisinternational.org
Fig. 1 Block diagram of system
Fig. 2 Flowchart of system
Community Impact Assessment Framework
A detailed impact assessment approach was created to assess the possible social, economic, environmental, and
sustainability effects of deploying solar-powered IoT environmental health monitoring systems in community
contexts. The evaluation employed a multi-faceted approach to analyze the role of community-based
environmental monitoring technology in advancing sustainable development goals and enhancing community
resilience. The evaluation framework was organized into four principal impact domains:(1) Social Impact-
community empowerment, environmental health awareness, and social cohesion effects; (2) Economic Impact -
cost-effectiveness, local economic opportunities, and healthcare cost implications; (3) Environmental
Sustainability - resource efficiency, carbon footprint reduction, and ecological benefits; and (4) Community
Resilience - adaptive capacity, disaster preparedness, and long-term sustainability outcomes.The data collection
encompassed the methodical recording of system deployment procedures, technical performance indicators,
community engagement trends, and resource usage assessments. The study integrated quantitative performance
metrics and qualitative observational data to deliver a thorough evaluation of community impact potential across
all sustainability aspects.
Data Collection Protocol
Data collection was conducted via a singular extensive field deployment and community evaluation, illustrating
the pilot aspect of this community environmental health intervention. The prototype system was implemented
for rigorous assessment during a singular field campaign, facilitating real-time technological validation
alongside the collection of social science data. Environmental monitoring data were gathered during the
deployment period, including temperature, humidity, air pressure, gaseous pollutants, and particulate matter
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1705
www.rsisinternational.org
concentrations. Simultaneous social data collection involved community interviews, participatory observations,
and survey administration to document instantaneous community reactions and alterations in environmental
health awareness due to access to real time environmental data.
Social Impact Assessment Methods
Based on multi-dimensional community impact assessment, the community impact was assessed using a
thorough sustainability evaluation approach that analyzed the possible social, economic, environmental, and
governance effects of solar-powered IoT environmental health monitoring devices. The evaluation incorporated
various assessment methods to deliver a comprehensive picture of the community advantages and problems
related to technology-enabled environmental health monitoring.The study methodically assessed the role of
community-based environmental health monitoring in advancing pertinent Sustainable Development Goals,
specifically:(1) SDG 3 (Good Health and Well-being): improved community access to environmental health
information that promotes preventative health measures and health equity; (2) SDG 6 (Clean Water and
Sanitation): enhanced environmental monitoring facilitating the management of water and air quality; (3) SDG
7 (Affordable and Clean Energy): integration of solar power to enhance renewable energy utilization in
community health initiatives; (4) SDG 11 (Sustainable Cities and Communities): Intelligent urban technologies
facilitating sustainable urban development and enhancing community resilience; (5) SDG 13 (Climate Action):
environmental surveillance facilitating climate adaption and mitigation strategies; (6) SDG 17 (Partnerships for
Goals): facilitating technology transfer and enhancing community capacity to promote multi-stakeholder
engagement.
The evaluation framework assessed four interrelated factors of sustainability: (1) Social Sustainability:
Empowering communities via access to environmental health data, enhancing social cohesion through collective
environmental monitoring, fostering environmental health literacy, and advocating for environmental justice
through democratized information access; (2) Economic Sustainability: a cost-effectiveness analysis comparing
community-based monitoring with traditional surveillance systems, potential healthcare cost reductions via
preventive health measures, local economic prospects through technology maintenance and data management,
and an evaluation of the long-term economic feasibility for community-scale implementation; (3) Environmental
Sustainability: evaluation of the carbon footprint of solar-powered monitoring systems, assessment of resource
efficiency encompassing material utilization and waste production, analysis of ecological impacts during
deployment and operation, and the role in environmental protection via enhanced monitoring capabilities; (4)
Governance and Institutional Sustainability: Enhancing community capacity for environmental health
governance, assessing integration with current public health infrastructure, evaluating policy implications for
community-based environmental surveillance, and establishing institutional frameworks that facilitate
sustainable technology adoption.
Data Analysis Approach
Technical performance data were examined through descriptive system reliability indicators to confirm
operational efficacy and sustainability. The community impact assessment employed a mixed-methods analytical
methodology that integrated quantitative performance indicators with qualitative effect evaluation across the
four pillars of sustainability.The analytical approach utilized sustainability impact assessment methodologies to
evaluate multi-dimensional community benefits, SDG indicator alignment analysis to measure contributions to
sustainable development objectives, and stakeholder impact analysis to assess benefits and challenges for various
community groups. Cross-dimensional analysis investigated the interrelations among social, economic,
environmental, and governance outcomes to yield a holistic knowledge of the consequences for community
sustainability.
Impact measurement concentrated on three principal outcome categories: (1) immediate technical outcomes -
system performance, reliability, and accessibility; (2) community process outcomes - engagement patterns,
capacity building, and institutional development; and (3) potential long-term impacts - sustainability
implications, scalability potential,and contributions to community resilience and sustainable development goals.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1706
www.rsisinternational.org
Ethical Considerations and Community Collaboration
The research protocol was created in collaboration with community stakeholders, guaranteeing cultural
sensitivity and community advantage. The informed consent processes encompassed both the acquisition of
technical data and involvement in social research. Community ownership of environmental health data was
achieved by transparent data-sharing policies and community access to all monitoring outcomes. Ethical
considerations encompassed safeguarding community privacy, ensuring equal access to research benefits, and
enhancing community capacity via technology transfer and environmental health education. The research design
employed community-based participatory research approaches, framing community members as partners instead
of subjects in environmental health monitoring and evaluation.
RESULT AND DISSCUSION
Technical Technical System Performance
The solar-powered IoT environmental health monitoring system exhibited strong technical performance during
the deployment period, maintaining continuous operation with effective real-time environmental monitoring and
data transmission capabilities crucial for community health applications. Figure 3 shows the prototype of system.
The system incorporated several high-precision sensors, including the AHT20 temperature-humidity sensor
(±0.3°C temperature accuracy, ±2% humidity accuracy), BMP280 barometric pressure sensor (±1 hPa absolute
accuracy), MQ-135 gas sensor for detecting CO₂, NH₃, and NOₓ gases, and GP2Y1014AU0F optical dust sensor,
which can detect particulate matter as small as 0.8 micrometers. The real-time data transmission to the
ThingsBoard IoT platform ensured sustained connectivity, as indicated by the ongoing status, reflecting
minimum system downtime. The mobile and web dashboard interfaces offered accessible real-time data
visualization, encompassing temperature readings (recorded high of 40.92°C with a spike to 41°C), humidity
levels (32% corresponding to temperature peaks), and dust density measurements (0.04 µg/m³ with fluctuations
indicating system sensitivity to particulate matter variations), thereby affirming the system's capability for
comprehensive monitoring of environmental health parameters, appropriate for diverse community user access.
Figure 4 shows the ThingsBoard dashboard
The cost-effectiveness analysis of the system indicated significant economic benefits, with total development
costs under RM 150. The selection of components emphasized an optimal cost-performance equilibrium, with
the ESP32-WROOM-32 microcontroller delivering integrated Wi-Fi and Bluetooth functionalities, thereby
obviating the need for supplementary communication modules typical of conventional Arduino-based systems.
Concurrently, advanced sensors (AHT20, BMP280) provided enhanced accuracy and reliability compared to
traditional alternatives (AHT10, BMP180) at similar price points. The integration of solar power has attained
effective energy autonomy with uninterrupted operational capability, demonstrated by consistent real-time data
gathering and transmission, hence confirming the sustainability model for extensive community-scale
implementation.
Fig. 3 Prototype of system
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1707
www.rsisinternational.org
Fig. 4 ThingsBoard dashboard
The system effectively showcased precise environmental monitoring with efficient data presentation on the
ThingsBoard platform, where integrated visualization tools allowed community members to access temperature
trends, humidity patterns, and dust density variations through user-friendly graphical interfaces available on
mobile applications and web browsers. Energy management optimization strategies ensured consistent sensor
functionality and data transmission under varying solar irradiance conditions, validating the system's potential
for sustainable, cost-effective operation that reduces dependence on non-renewable energy sources while
facilitating reliable environmental health monitoring crucial for informed health-protective decision-making.
Social Impact Outcomes
The deployment exhibited considerable potential for improving community involvement in environmental health
decision-making by providing democratized access to real-time air quality data that was previously inaccessible
to community members. Before the establishment of the system, the study community lacked access to localized
environmental health data, depending instead on regional air quality statistics that failed to represent specific
neighborhood conditions or pollution patterns. The execution of community-based monitoring mitigated the
disparity in environmental health information by supplying real-time, localized environmental data, which
facilitated informed health-protective actions during pollution incidents and laid the groundwork for community
environmental health awareness and empowerment.
The community's access to continuous air quality monitoring significantly improved environmental health
awareness, since the availability of real-time data allowed for instant recognition of pollution variations that had
previously gone unnoticed by residents. The accessible dashboard enabled the visual presentation of data,
enhancing comprehension of air quality trends and their correlations with daily activities, meteorological
conditions, and possible pollution sources, thereby converting abstract environmental health ideas into concrete,
actionable insights. Spontaneous informal community talks regarding environmental health concerns arose
during system operation, reflecting an increasing community interest in environmental quality and health
protection initiatives. These discussions marked the preliminary phases of developing community environmental
health literacy, as community members started to contextualize air quality data in relation to their lived
experiences and health issues.
The system deployment facilitated significant enhancements in social cohesion and collective action capacity
within the community's environmental health framework. Collaborative access to environmental monitoring data
established a unified reference for community environmental issues, promoting discussions among residents
regarding air quality, pollution sources, and possible joint actions to address environmental health hazards. The
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1708
www.rsisinternational.org
technological demonstration initiated significant conversations around community ability for environmental
self-monitoring and the possibility to enhance monitoring capacities to tackle additional environmental health
issues, including noise pollution and water quality. The results demonstrated significant potential for creating
community-based environmental health advocacy networks and fostering sustainable community involvement
in environmental health protection initiatives, with numerous community members showing interest in
establishing permanent monitoring systems and community environmental health committees.
Economic Influence and Sustainability
The examination of economic sustainability demonstrated considerable benefits of community-based
environmental health monitoring over conventional surveillance methods, which generally necessitate
substantial capital investment and continuous operational costs. The RM 150 system development cost set an
attainable price point for community-scale implementation, allowing for feasible replication across several
community locations or adoption by budget-constrained organizations. The analysis of operational costs
revealed considerable long-term economic advantages, as solar power autonomy resulted in negligible electricity
expenses, hence reducing continuous energy costs that would otherwise accrue significantly over prolonged
operational durations. Maintenance needs were minimal, mostly consisting of infrequent sensor calibration tasks
that could be executed by community members with fundamental training, along with regular cleaning of solar
panels and sensor inlets to ensure optimal performance. This low-maintenance design decreased total ownership
costs and improved the viability of ongoing community operation without necessitating specialist technical skills
or significant continuous financial investment.
An evaluation of healthcare cost implications revealed significant potential for preventive health advantages
through early warnings of pollution exposure, allowing community members to undertake protective measures
such as restricting outdoor activities, utilizing air filtration systems, or temporarily relocating at-risk family
members during severe pollution incidents. The accessibility of localized environmental health data improved
community health planning by revealing pollution trends, peak exposure periods, and at-risk areas, so facilitating
targeted health interventions and environmental health education initiatives. Projected long-term savings in
healthcare costs are anticipated through enhanced environmental health awareness and proactive health-
protective decision-making, potentially leading to reductions in pollution-related respiratory diseases,
cardiovascular issues, and emergency healthcare usage.
Local economic opportunities arose through various avenues, including the potential for technology transfer to
enhance community technical capacity in environmental monitoring technology, sensor maintenance, and data
interpretation skills, which could lead to employment prospects in the environmental health sector. The
extension of the community-based monitoring network has generated chances for scaling implementation across
several neighborhoods or communities, potentially leading to the establishment of local social enterprises
dedicated to environmental health monitoring services. The establishment of local maintenance and support
services for environmental health technology applications may create income opportunities for community
members, while ensuring the continuous operation of systems. Additionally, educational and training programs
related to environmental health technology could augment community human capital and enhance employability
in expanding environmental technology sectors.
Evaluation of Environmental Sustainability
The assessment of environmental sustainability revealed significantly favorable results across many
sustainability indices, confirming the ecological suitability of community-based environmental health
monitoring methods. The integration of solar power facilitated efficient renewable energy operations, resulting
in a net positive environmental impact by eliminating greenhouse gas emissions linked to traditional grid
electricity usage. The sustained operational capacity exhibited during deployment confirmed the feasibility of
fully autonomous, ecologically friendly community health monitoring, entirely powered by renewable energy
sources.
The energy efficiency analysis indicated ideal performance, with recorded power consumption patterns
facilitating prolonged autonomous operation via the solar power subsystem. The 20-watt solar panel capacity
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1709
www.rsisinternational.org
sufficiently generated energy for the system's operating needs, encompassing sensor measurements, data
processing, wireless transmission, and local display functionalities. The energy efficiency was achieved through
meticulous component selection prioritizing low-power operation, sophisticated power management techniques
such as sensor duty cycling and optimized data transmission protocols, and effective solar charging systems that
maximized energy capture and storage under diverse weather conditions in the tropical Malaysian climate.
The implementation markedly improved environmental monitoring capabilities in the study area by enhancing
the spatial resolution of air quality assessments, thereby capturing localized pollution patterns absent in regional
monitoring stations situated several kilometers away from the community. The real-time continuous monitoring
capacity offered detailed temporal resolution, facilitating the discovery of brief pollution incidents and daily
patterns that coarse temporal sampling would overlook. The availability of community-level environmental
data, previously absent in the study area, significantly enhanced local environmental health surveillance
capabilities and established baseline data for evaluating the efficacy of pollution mitigation initiatives or
monitoring changes in environmental quality over time.
The ecological impact evaluation verified a negligible environmental footprint from the installation and
operation of the system, employing non-invasive mounting techniques that preserved soil integrity and habitat,
while integrating wildlife-safe design elements to avert entrapment or collision hazards. The selection of
sustainable materials for weather-resistant housing emphasized durable, recyclable options that reduce waste
creation at the end of their life cycle while ensuring long-term resistance to environmental exposure. The
selection of components prioritized the availability of recyclable materials to enable sustainability at the end of
life, ensuring responsible disposal or repurposing when system components needed replacement.
Contribution to Sustainable Development Goals
The systematic assessment of SDG alignment indicated significant contributions across six principal sustainable
development domains, illustrating the multi-faceted sustainability impact of community-based environmental
health monitoring systems and their ability to concurrently tackle various global development issues. SDG 3
(Good Health and Well-being) demonstrated the most robust and direct correlation via improved community
access to environmental health information, which facilitates preventive health measures, early warning systems
for pollution exposure, and bolstered community capacity for health-protective decision-making. The
implementation resulted in a 100% enhancement in community access to real-time air quality data compared to
the baseline of no localized environmental health information, enabling immediate awareness of pollution
exposure for community health protection and fostering improved community capacity for environmental health
risk assessment that was previously unattainable without relevant environmental data.
The contributions to SDG 7 (Affordable and Clean Energy) were evidenced by the successful integration of
renewable energy in community health initiatives, achieving effective solar energy independence during
implementation and offering a practical demonstration of solar power's feasibility for health technology
applications in tropical climates. The off-grid operational capacity confirmed sustainable energy solutions for
areas with restricted or intermittent electricity access, tackling energy poverty while concurrently advancing
health improvement goals. The economical renewable energy model created a framework for perpetual
community health monitoring applications that can function indefinitely without grid connectivity or fuel
expenses, showcasing viable methods for the sustainable implementation of community health technology in
accordance with global renewable energy transition goals.
The alignment with SDG 11 (Sustainable Cities and Communities) was established through IoT-enabled
environmental health monitoring, showcasing affordable smart city technologies that emphasized community
advantages over technological complexity. The community-centered design advocated for inclusive smart city
development, ensuring technology addresses community needs instead of imposing intricate systems
necessitating specialized knowledge. It bolstered community resilience by enhancing environmental health
surveillance capabilities, facilitating proactive responses to environmental health issues, and supported
sustainable urban development through community-based monitoring that supplies local environmental data
critical for evidence-based urban planning and environmental management decisions.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1710
www.rsisinternational.org
Contributions to SDG 13 (Climate Action) encompassed the augmentation of community capacity for
monitoring climate-related environmental health, including the detection of heat stress via temperature and
humidity assessments, the tracking of climate-sensitive air quality trends, and the documentation of
environmental alterations potentially associated with climate variability. Real-time environmental data
facilitated community climate adaption efforts by identifying sensitive periods, regions, and groups necessitating
increased protection during climate-related health difficulties. The solar-powered initiative directly facilitated
climate mitigation by promoting renewable energy use, which replaced potential fossil fuel consumption,
diminished carbon emissions through sustainable monitoring technology that modeled low-carbon strategies for
community health protection, and enhanced community environmental awareness that fostered broader climate
action participation and behavioral transformation.
Further contributions to SDG 6 (Clean Water and Sanitation) were established through extensive monitoring of
environmental parameters, which laid the groundwork for integrated environmental health surveillance that
could be expanded to include water quality assessment. Additionally, community-based monitoring models were
demonstrated, utilizing analogous technological methods and community engagement strategies for water
quality monitoring. Contributions to SDG 17 (Partnerships for Goals) arose from technology transfer models
that fostered collaborations among communities, universities, and governments for sustainable health initiatives.
These included community capacity building via the application of environmental health technologies that
improved local expertise, frameworks for knowledge sharing in community environmental health monitoring
adaptable to various contexts, and stakeholder engagement models for sustainable technology deployment that
exemplified effective cooperation among research institutions, community organizations, and local government
bodies.
Integration of Community Sustainability Impact
The social sustainability study showed strong community interest and involvement with environmental health
monitoring technologies during implementation, indicating community empowerment potential. Community
members actively sought air quality measurements, asked about pollution levels' health effects, and requested
continuous access to environmental health data beyond the project. The implementation ensured equitable
access to data, making environmental health information available regardless of socioeconomic status,
educational background, or digital literacy, upholding environmental justice in equitable health protection.
Accessible technology for older people with low computer skills, kids interested in environmental technology,
and families anxious about their children's lung health helped social inclusion. System exposure and community
involvement improved community technical and environmental health literacy, allowing community members
to discuss air quality concepts, analyze environmental data, and link environmental conditions to health
outcomes.
Economic sustainability was assessed using a low-cost implementation methodology suitable for community-
scale adoption, requiring minimum external funds or subsidies beyond the initial capital outlay. Reducing
pollution exposure and implementing early health interventions could save healthcare costs and significantly
reduce healthcare utilization, especially for at-risk groups like asthmatic children and elderly cardiovascular
disease patients. Technology maintenance, data analysis, and environmental health education can boost local
economies beyond health improvements. Solar power autonomy ensures long-term resource efficiency and
financial sustainability with minimal continuous operational expenses and a lifespan exceeding five years before
significant component replacement. The review showed a high social return on investment through community
health gains, environmental knowledge, and community competence beyond financial measurement.
Environmental sustainability showed exceptional resource conservation via renewable energy operations,
eliminating fossil fuel usage linked to grid electricity and minimizing electronic waste through durable, long-
lasting components. Environmental benefits from improved monitoring capacity included identifying pollution
sources, documenting pollution trends to inform mitigation strategies, and community advocacy for
environmental preservation based on empirical environmental data. The non-invasive monitoring method
preserved ecological harmony while enabling the use of eco-friendly community health technology that
improved environmental quality.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1711
www.rsisinternational.org
Governance and institutional sustainability assessments showed greater community capacity for environmental
health decision-making due to improved access to environmental information, enabling informed civic
engagement in policy discussions and planning. Compatibility with public health surveillance goals, data
exchange with municipal environmental management systems, and alignment with national environmental health
monitoring frameworks show significant integration potential with current public health infrastructure. The
implementation provided a pragmatic framework for community-based environmental health policy based on
local environmental data and community priorities rather than top-down regulatory techniques. University
researchers, community organizations, and local governments collaborated to create a multi-stakeholder
framework for sustainable technology deployment that demonstrated effective community environmental health
monitoring methods beyond the research phase.
Discussion
The implementation of this solar-powered IoT environmental health monitoring system has considerable
potential for mitigating environmental justice issues and augmenting community empowerment via equitable
access to environmental health data. The economic feasibility, along with free operational electricity expenses
from solar autonomy and little maintenance needs, facilitates significantly enhanced environmental health
monitoring coverage with authentic community ownership, independent of ongoing external support. The
technical validation verified high-precision measurements appropriate for community health decision-making
(AHT20: ±0.3°C, ±2% humidity; BMP280: ±1 hPa; particulate detection: 0.8 μm), while the successful
integration of the ThingsBoard platform with user-friendly mobile and web interfaces illustrated that cost-
effective IoT technologies can deliver accessible environmental health data across varying literacy levels.
Outcomes of community empowerment demonstrate that accessible environmental health data significantly
increases community agency by converting members from passive recipients of external information to active
participants in environmental health surveillance. Improvements in social cohesion and spontaneous community
discussions indicate that shared environmental monitoring data acts as a catalyst for collective action regarding
environmental health protection.
The assessment of environmental sustainability indicated that community-based monitoring can be executed in
ecologically responsible manners that harmonize health enhancement with climate action and environmental
conservation objectives. The efficacy of solar energy autonomy confirms the feasibility of renewable energy for
community health applications in tropical climates, while the negligible ecological footprint from non-invasive
installations and the use of recyclable materials illustrates that environmental health monitoring improves rather
than diminishes environmental quality. The system's impact on six Sustainable Development Goals (SDGs 3,
6, 7, 11, 13, 17) exemplifies a multi-faceted sustainability effect, notably in Good Health and Well-being via a
100% enhancement in community access to real-time air quality data, Affordable and Clean Energy through
evidenced renewable energy adoption, and Sustainable Cities and Communities through the execution of
inclusive smart city technologies. Benefits of climate adaptation encompass improved community capability to
monitor heat stress, analyze climate-sensitive air quality trends, and proactively address climate-related
environmental health issues, while renewable energy operations facilitate climate mitigation by reducing fossil
fuel consumption. The improved spatial and temporal precision of community-level monitoring delivers
localized environmental data crucial for evidence-based climate adaptation planning, addressing neighborhood-
scale impacts overlooked by regional monitoring networks.
Technical Limitations and Challenges
During deployment, the system performed well, however numerous technical constraints should be
acknowledged for balanced assessment and improvement. Systematic sensor calibration is needed to maintain
measurement accuracy during long operational durations. The cost-effective MQ-135 gas sensor is suitable for
relative air quality monitoring, but baseline drift requires periodic recalibration to preserve absolute
measurement accuracy. Sensor response is affected by temperature and humidity, requiring temperature
correction algorithms or reference standard calibration. Optical dust sensor (GP2Y1014AU0F) sensitivity to
ambient light and airflow patterns demands careful setup and periodic cleaning to prevent measurement
degradation from dust collection on optical surfaces. To maintain measurement reliability for community health
applications, future implementations should include automated calibration processes, temperature adjustment
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1712
www.rsisinternational.org
algorithms, and periodical validation against certified reference devices.
Beyond sensor accuracy, data reliability includes completeness, temporal resolution, and quality assurance.
Network connectivity difficulties can disrupt data transfer, especially in places with intermittent Wi-Fi or during
community network infrastructure power outages. During significant pollution incidents, neighborhood Wi-Fi
networks may fail, causing data gaps. Local data buffering with automatic retry methods, 4G/LTE modules for
cellular backup connectivity, and edge computing for preliminary data processing would improve network
resilience. Automated anomaly detection systems should detect sensor malfunctions, transmission faults, and
environmental circumstances outside typical operating ranges to allow timely maintenance before data quality
degrades.
Waterproofing, extreme weather protection, and material deterioration are environmental exposure challenges.
High humidity, intense sun radiation, and sometimes heavy rainfall test protective enclosures and electrical
connections in tropical Malaysia. Long-term outdoor exposure may degrade solar panel efficiency, battery
capacity, and electronic component age, reducing system longevity and reliability. IP67-rated enclosures,
conformal coating for circuit boards, corrosion-resistant materials for outdoor components, and active thermal
management for high-temperature electronics should be included in future designs. Battery health monitoring
with replacement schedules, solar panel cleaning to maintain charging efficiency, connector inspection for
corrosion prevention, and sensor housing integrity verification should be part of preventive maintenance to
ensure system reliability over time.
Cost-Benefit Analysis and Scalability
Comprehensive cost-benefit analysis shows community-scale implementation has positive economics with
deployment scenario and operational context sensitivity. The basic implementation cost of RM 150 per unit
makes community adoption affordable, saving 95% compared to commercial environmental monitoring stations
(RM 3,000–10,000). However, scale adds cost dimensions that require rigorous study. For 5-10 units serving a
neighborhood, per-unit expenses are near the baseline with minor economies of scale, total investment is RM
750-1,500, and community fundraising, local government funding, or university partnerships make
implementation possible. Bulk component procurement saves 15-20%, centralized data infrastructure (cloud
hosting, advanced analytics platforms) adds RM 2,000-5,000 annually, and technical support requires part-time
coordinator positions (estimated RM 15,000-25,000 annually), totaling RM 6,000-12,000 for equipment and
operational costs for medium-scale deployment (50-100 units covering a municipality). For large-scale
deployment (500+ units across multiple municipalities or regions), economies of scale reduce component costs
by 25-30%, dedicated technical team requirements include full-time system administration, data analysis, and
community liaison positions (estimated RM 100,000-200,000 annually), and centralized calibration facilities and
quality assurance programs add infrastructure costs (RM 50,000-100,000 initial investment).
Benefit quantification includes various elements of direct and indirect community value. Early warning
capabilities can reduce pollution exposure by 20-30% for responsive community members, and reduced
respiratory emergency visits, asthma exacerbations, and cardiovascular events can save healthcare costs,
conservatively estimated at RM 500-1,000 per at-risk individual annually based on air pollution health impacts
literature. Improved environmental health literacy and empowerment with unquantifiable but substantial
community capacity building value, increased property values in neighborhoods with environmental monitoring
and health protection infrastructure (literature suggests 2-5% premiums for environmental amenities), and
improved community cohesion and collective efficacy with social capital benefits extending beyond health
outcomes to boost institutional benefits include data value for public health surveillance, urban planning, and
environmental management that exceeds equipment costs, research partnerships and academic collaboration that
increase knowledge production, and policy advocacy that empowers communities to influence local
environmental regulations and enforcement priorities using empirical evidence.
Changes in assumptions affect cost-effectiveness across implementation scenarios in sensitivity analysis. Ideal
scenario assumptions include 30% bulk purchasing cost reduction, 40% pollution exposure reduction through
behavioral adaptation, and RM 1,500 annual healthcare savings per at-risk individual, resulting in medium-scale
deployment break-even at 2-3 years and a 5:1 benefit-cost ratio over five years. The pessimistic scenario assumes
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1713
www.rsisinternational.org
10% cost increase from implementation challenges, 10% exposure reduction due to limited behavioral change,
and RM 300 annual healthcare savings with conservative health impact estimates, resulting in break-even at 8-
10 years for medium-scale deployment and 1.2:1 marginal benefit-cost ratio over five based on literature
consensus, realistic mid-range scenario assumptions include 15-20% bulk purchasing savings, 20-25% exposure
reduction with moderate community engagement, and RM 700-900 annual healthcare savings, resulting in break-
even at 4-6 years for medium-scale deployment and a 2.5:1 benefit-cost ratio over five years These possibilities
are economically viable under reasonable assumptions, but health benefit quantification and behavioral response
parameters need longitudinal implementation study to resolve the biggest uncertainty.
Implementation Strategies: Training, Maintenance, and Policy Integration
Community training initiatives must address technical proficiency, environmental health knowledge, and
sustainable operational capability for large-scale implementation. We recommend Level 1 (Community User
Training) for general community members, which covers dashboard interpretation, air quality indices, health
effects of different pollution levels, and protective actions during high pollution episodes in 2-hour community
workshops with multilingual materials for diverse educational backgrounds. Level 2 (Community Monitor
Training) for volunteer community monitors covers system operation and troubleshooting, routine maintenance
(sensor cleaning, battery checks), data interpretation and quality assessment, and community reporting protocols
in a 1-day hands-on course with mentorship and quarterly refresher sessions. Level 3 (Technical Coordinator
Training) for dedicated technical staff covers advanced system configuration and optimization, sensor calibration
and quality assurance protocols, data analysis and reporting systems, and coordination with public health
authorities and researchers in 3-5 days with certification and ongoing professional development.
Training content should emphasize practical skills and community relevance through culturally appropriate
materials reflecting local environmental health concerns and community communication norms, hands-on
practice with actual equipment to ensure competence before independent operation, and locally relevant case
studies and examples connecting abstract concepts to familiar community experiences. In-person workshops for
practical skill development and community building, online resources and video tutorials for self-paced learning
and reference, and peer learning networks for trained community members to support and share knowledge
should maximize accessibility and engagement. Effective training should be measured by pre- and post-training
knowledge assessments, practical skills demonstrations, and follow-up surveys and observations to ensure
knowledge retention and application in community practice. Community capacity building includes leadership
development to create environmental health champions who can mobilize the community, organizational
development to strengthen community environmental health committees or working groups, and advocacy skills
training to help communities communicate with policymakers and government agencies on environmental health
issues.
Technical requirements must be balanced with community capability and resource limits for sustainable
maintenance. Monthly visual inspections of physical components (enclosures, solar panels, connections),
quarterly sensor cleaning and basic calibration checks by trained community monitors, and annual
comprehensive system audits by technical coordinators with full calibration validation should be part of
preventive maintenance protocols. Corrective maintenance procedures should outline protocols for community
monitors to identify common issues (connectivity issues, sensor anomalies), technical coordinators to diagnose
and resolve moderate technical issues, and external technical support for component replacement or complex
repairs requiring specialized expertise or equipment. To reduce downtime, spare parts inventory management
requires strategic stockpiling of consumables (batteries, sensors with limited lifespan), common failure
components (cables, connectors, solar charge controllers), and rapid procurement of less common replacement
needs through suppliers or regional technical centers.
Automated data validation algorithms to flag anomalous readings, inter-sensor comparison protocols for
networks with multiple units to identify calibration drift, and periodic validation against reference instruments
to trace measurement standards ensure data reliability and community trust. Real-time system health monitoring
(battery voltage, connectivity status, data transmission rates) with automated alerts for technical issues,
centralized data quality dashboards aggregating quality metrics across monitoring networks, and predictive
maintenance algorithms identifying sensors approaching calibration intervals or component replacement needs
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1714
www.rsisinternational.org
enable proactive maintenance. Regular surveys of community monitors and users, technical support logs
documenting maintenance issues and resolutions, and community advisory committees providing input on
system performance and needed improvements should capture operational challenges and user experiences,
creating continuous improvement cycles that adapt systems to changing community needs and operational
conditions.
Community monitoring must be integrated into policy to sustain public health effect and institutional
transformation. Local government integration should include formal data sharing agreements between
community monitoring networks and municipal environmental management agencies, community-generated
data in official air quality reporting and public health surveillance systems, and collaborative response protocols
for pollution episodes identified by community monitoring, involving local authorities in timely investigation
and mitigation. Regulatory framework development should recognize community monitoring data in
environmental compliance and enforcement proceedings, establish quality standards and certification programs
for community monitoring systems to ensure data credibility, and protect community environmental health
advocates from interference or retaliation. Municipal public health budgets should support community
environmental health monitoring infrastructure and training, environmental health block grants and formula
funding should include community monitoring, and public-private partnerships should leverage corporate
environmental responsibility commitments to fund community monitoring in industrial emission-affected areas.
Community organisations leading monitoring initiatives, academic institutions providing technical support and
research collaboration, public health agencies using data for surveillance and programme planning, and
environmental advocacy organisations amplifying community voices in policy processes should work together
under multi-stakeholder collaboration frameworks. Community-led governance boards with decision-making
authority over data use and system operations, transparent data policies ensuring community access while
addressing privacy and security concerns, and equitable benefit sharing must ensure that communities generating
data receive primary benefits like health protection, capacity building, and policy influence (rather than
integrating environmental health monitoring and education into community health worker programs, integrating
with community-based participatory research initiatives to create ongoing university-community partnerships,
and developing social enterprise models where community monitoring networks provide fee-for-service data to
government agencies or industries with revenues are long-term institutionalization strategies.
CONCLUSIONS
This study designed and verified a solar-powered IoT system for environmental health monitoring that could
increase community awareness, empowerment, and sustainable development. The system performed well with
accurate sensor measurements, reliable real-time data transfer via the ThingsBoard platform, and efficient solar
energy autonomy for continuous autonomous operation. It was economically viable with RM 150 compared to
commercial alternatives and had no operational electricity expenditures. The deployment gave the community
increased agency through democratized access to environmental health data, social cohesion that promotes
collective action for environmental health, alignment with six Sustainable Development Goals (notably SDG 3,
7, and 11), and environmental justice by reducing information disparities that affect vulnerable populations. The
use of renewable energy has proven ecologically sustainable community health monitoring, which reduces fossil
fuel consumption and improves community ability to handle climate-related environmental health issues. The
findings propose a repeatable community-based environmental health monitoring paradigm that integrates
technical innovation, social impact, economic sustainability, and environmental preservation. This approach
provides practical ways to improve community environmental health surveillance, empowerment, and equity.
Future research must focus on longitudinal studies that assess sustained community adoption and measurable
improvements in health outcomes. It should also include comparative effectiveness research across various
community contexts and demographic groups, exploration of optimal integration models that link community
monitoring with public health infrastructure, creation of sustainable funding frameworks for long-term
community operations, and policy research that investigates institutional mechanisms for integrating
community-generated environmental health data into official surveillance systems. These efforts aim to enhance
evidence-based approaches to community environmental health monitoring, supporting both public health
protection and sustainable community development goals.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 1715
www.rsisinternational.org
ACKNOWLEDGMENT
The author expresses gratitude to Universiti Teknikal Malaysia Melaka (UTeM) for its financial support.
REFERENCES
1. Jo, J., Jo, B., Kim, J., & Choi, I. (2020). Implementation of IoT-based air quality monitoring system for
investigating particulate matter (PM10) in subway tunnels. International Journal of Environmental
Research and Public Health, 17(15), 5429.
2. Peixe, J. and Marques, G. (2024). Low-cost IoT-enabled indoor air quality monitoring systems: a
systematic review. Journal of Ambient Intelligence and Smart Environments, 16(2), 167-180.
3. Saravanakumar, S., A, B., P, D., Janani, T., & Saravana, I. (2024). Solar energy powered advanced smart
streetlight for remote areas. Int Res J Adv Engg Hub, 2(04), 1003-1009.
4. Li, Y., Sun, Z., Huang, M., Sun, L., Liu, H., & Lee, C. (2024). Self‐sustained artificial internet of things
based on vibration energy harvesting technology: toward the future eco‐society. Advanced Energy and
Sustainability Research, 5(11).
5. Dosymbetova, G., Mekhilef, S., Orynbassar, S., Kapparova, A., Saymbetov, A., Nurgaliyev, M., … &
Koshkarbay, N. (2023). Neural network based active cooling system with IoT monitoring and control for
lcpv silicon solar cells. IEEE Access, 1-1.
6. Múnera, D., Tobón, D., Aguirre, J., & Gómez, N. (2021). IoT-based air quality monitoring systems for
smart cities: a systematic mapping study. International Journal of Electrical and Computer Engineering
(IJECE), 11(4), 3470.
7. Ng, W. and Dahari, Z. (2020). Enhancement of real-time iot-based air quality monitoring system.
International Journal of Power Electronics and Drive Systems (IJPEDS), 11(1), 390.
8. Shashank, G., Lohit, V., Venkata, G., & Vishal, S. (2022). IoT Based Air Quality Monitoring System.
Technoarete Transactions on Internet of Things and Cloud Computing Research, 2(1).
9. Jose, A., Abraham, C., Soman, A., Ajumal, T., & Shibu, A. (2024). IoT based solar powered air purifier
with air quality monitoring system. E3s Web of Conferences, 529, 04016.
10. Mondal, D. and Banerjee, A. (2022). Implementation of IoT for air quality surveillance. IJEAST, 7(8),
151-159.
11. Zhou, M., Abdulghani, A., Imran, M., & Abbasi, Q. (2020). Internet of things (iot) enabled smart indoor
air quality monitoring system., 89-93.
12. Taştan, M. (2022). A low-cost air quality monitoring system based on internet of things for smart homes.
Journal of Ambient Intelligence and Smart Environments, 14(5), 351-374.
13. Jahandar, M., Kim, S., & Lim, D. (2021). Indoor organic photovoltaics for self‐sustaining iot devices:
progress, challenges and practicalization. Chemsuschem, 14(17), 3449-3474.
14. Lin, L., Chen, Z., Wang, Y., & Jiang, L. (2022). Improving anomaly detection in IoT-based solar energy
system using smote-pso and svm model. 360, 123-131.
