Pengembangan Prototipe Aplikasi Augmented Reality (AR) untuk Pemantauan dan Analisis Kondisi Lingkungan Secara Real-Time Berbasis IoT

Diah Aryani; Habibullah  Akbar; Indri  Handayani

Authors

Diah Aryani Universitas Esa Unggul Jakarta
Habibullah Akbar Universitas Esa Unggul Jakarta
Indri Handayani Universitas Esa Unggul Jakarta

Keywords:

Augmented Reality, Internet of Things, Pemantauan Lingkungan, Smart Environment

Abstract

Penelitian ini bertujuan untuk mengembangkan prototipe aplikasi Augmented Reality Monitoring for Environmental Analysis (ARMAN) sebagai solusi inovatif untuk pemantauan dan analisis kondisi lingkungan secara real-time. Aplikasi ini dirancang untuk membantu masyarakat dan lembaga pemerintah dalam meningkatkan efisiensi pengelolaan lingkungan serta kesadaran akan kualitas udara, suhu, kelembaban, dan pengelolaan limbah. Sistem ARMAN dibangun melalui integrasi teknologi Internet of Things (IoT), komputasi awan, dan Augmented Reality (AR) untuk menghasilkan sistem yang interaktif, informatif, dan adaptif. Metodologi penelitian mencakup lima tahap utama, yaitu konsep, desain, pengembangan, pengujian, dan evaluasi. Sensor DHT11 dan MQ-135 digunakan untuk mendeteksi parameter suhu, kelembapan, dan kualitas udara, dan data tersebut kemudian dikirim ke Firebase Cloud Database melalui mikrokontroler ESP32 secara berkala. Data yang disimpan diproses dan ditampilkan secara visual melalui aplikasi AR berbasis Unity 3D dan SDK Vuforia, yang memungkinkan pengguna melihat informasi lingkungan dalam bentuk overlay interaktif. Selain itu, panel admin backend berbasis web disediakan untuk lembaga pemerintah atau pengelola lingkungan untuk memantau data agregat, tren, dan laporan historis dari berbagai titik sensor. Hasil uji coba menunjukkan bahwa sistem ARMAN mampu menampilkan informasi lingkungan secara real-time, akurat, dan menarik, serta mendukung kolaborasi antara masyarakat umum dan otoritas dalam pemantauan lingkungan. Penelitian ini membuktikan bahwa kombinasi teknologi IoT, cloud, dan AR dapat diimplementasikan secara efektif dalam sistem pemantauan lingkungan dan berpotensi menjadi dasar pengembangan lingkungan cerdas menuju implementasi konsep kota cerdas yang berkelanjutan.

Downloads

Download data is not yet available.

References

S. Shahid et al., “Innovations in Air Quality Monitoring: Sensors, IoT and Future Research,” Sensors 2025, Vol. 25, vol. 25, no. 7, Mar. 2025, doi: 10.3390/S25072070.

S. Lipiński, J. Piotrowski, and T. Olkowski, “Mobile air quality monitoring station - a solution for better pollution control,” Tech. Sci., Dec. 2025, doi: 10.31648/TS.11507.

S. P. Pathak, A. K. Singh, and S. Gokulanathan, “A Low-Cost IoT-Based Real-Time Air Quality Monitoring System Using Multi-Sensor Integration and Bluetooth Communication,” 2025 Int. Conf. Sensors Relat. Networks, SENNET 2025 - Spec. Focus Digit. Healthc., 2025, doi: 10.1109/SENNET64220.2025.11135994.

V. Shakhov and O. Sokolova, “Probabilistic Clustering for Data Aggregation in Air Pollution Monitoring System,” Sensors, vol. 25, no. 23, Dec. 2025, doi: 10.3390/S25237285.

I. G. A. I. F. Ramadhani et al., “IoT Implementation for Air Quality Monitoring System using Low Cost Sensor,” Proc. 2025 IEEE Int. Conf. Ind. 4.0, Artif. Intell. Commun. Technol. IAICT 2025, pp. 621–627, 2025, doi: 10.1109/IAICT65714.2025.11100335.

A. Alzahrani, P. Kostkova, H. Alshammari, S. Habibullah, and A. Alzahrani, “Intelligent integration of AI and IoT for advancing ecological health, medical services, and community prosperity,” Alexandria Eng. J., vol. 127, pp. 522–540, Aug. 2025, doi: 10.1016/J.AEJ.2025.05.046.

Y. Zhang, P. Geng, C. B. Sivaparthipan, and B. A. Muthu, “Big data and artificial intelligence based early risk warning system of fire hazard for smart cities,” Sustain. Energy Technol. Assessments, vol. 45, Jun. 2021, doi: 10.1016/j.seta.2020.100986.

L. Andeobu, S. Wibowo, and S. Grandhi, “Artificial intelligence applications for sustainable solid waste management practices in Australia: A systematic review,” Sci. Total Environ., vol. 834, Aug. 2022, doi: 10.1016/j.scitotenv.2022.155389.

X. Zhang, K. Shu, S. Rajkumar, and V. Sivakumar, “Research on deep integration of application of artificial intelligence in environmental monitoring system and real economy,” Environ. Impact Assess. Rev., vol. 86, Jan. 2021, doi: 10.1016/j.eiar.2020.106499.

T. I. Ladykova, E. I. Sokolova, L. Y. Grebenshchikova, R. G. Sakhieva, N. I. Lapidus, and Y. V Chereshneva, “Augmented reality in environmental education: A systematic review,” EURASIA J. Math. Sci. Technol. Educ., vol. 2024, no. 8, p. 2488, 2024, doi: 10.29333/ejmste/14914.

A. Garcia, Y. Saez, I. Harris, X. Huang, and E. Collado, “Advancements in air quality monitoring: a systematic review of IoT-based air quality monitoring and AI technologies,” Artif. Intell. Rev. 2025 589, vol. 58, no. 9, pp. 275-, Jun. 2025, doi: 10.1007/S10462-025-11277-9.

M. Marć, M. Tobiszewski, B. Zabiegała, M. de la Guardia, and J. Namieśnik, “Current air quality analytics and monitoring: A review,” Anal. Chim. Acta, vol. 853, no. 1, pp. 116–126, 2015, doi: 10.1016/J.ACA.2014.10.018.

J. Reis, D. Lopes, D. Graça, A. P. Fernandes, A. I. Miranda, and M. Lopes, “Using low-cost sensors to assess real-time comfort and air quality patterns in indoor households,” Environ. Sci. Pollut. Res., vol. 30, no. 3, pp. 7736–7751, Jan. 2023, doi: 10.1007/S11356-022-22771-W.

H. Relvas, D. Lopes, and J. M. Armengol, “Empowering communities: Advancements in air quality monitoring and citizen engagement,” Urban Clim., vol. 60, p. 102344, Mar. 2025, doi: 10.1016/J.UCLIM.2025.102344.

S. Bashath, N. Perera, S. Tripathi, K. Manjang, M. Dehmer, and F. E. Streib, “A data-centric review of deep transfer learning with applications to text data,” Inf. Sci. (Ny)., vol. 585, pp. 498–528, Mar. 2022, doi: 10.1016/J.INS.2021.11.061.

V. Braun, V. Clarke, N. Hayfield, and G. Terry, “Thematic analysis,” Handb. Res. Methods Heal. Soc. Sci., pp. 843–860, Jan. 2019, doi: 10.1007/978-981-10-5251-4_103.

L. Bryant and B. Hemsley, “Augmented reality: a view to future visual supports for people with disability,” Disabil. Rehabil. Assist. Technol., vol. 19, no. 3, pp. 800–813, 2024, doi: 10.1080/17483107.2022.2125090.

L. S. Nielsen, L. Skov, and H. Jensen, “Visual dysfunctions and ocular disorders in children with developmental delay. I. Prevalence, diagnoses and aetiology of visual impairment,” Acta Ophthalmol. Scand., vol. 85, no. 2, pp. 149–156, Mar. 2007, doi: 10.1111/J.1600-0420.2006.00867.X.

A. Vahabzadeh, N. U. Keshav, J. P. Salisbury, and N. T. Sahin, “Improvement of attention-deficit/hyperactivity disorder symptoms in school-aged children, adolescents, and young adults with autism via a digital smartglasses-based socioemotional coaching aid: Short-term, uncontrolled pilot study,” JMIR Ment. Heal., vol. 5, no. 2, Apr. 2018, doi: 10.2196/MENTAL.9631.

S. M. Rao and B. Gagie, “Learning through Seeing and Doing,” Teach. Except. Child., vol. 38, no. 6, pp. 26–33, Jul. 2006, doi: 10.1177/004005990603800604.

A. O. Alkhamisi et al., “Reality to Treat,” Proc. 2nd IEEE ACM Int. Work. Augment. Real., vol. 3, no. 1, pp. 31–37, 2004, Accessed: Dec. 24, 2025. [Online]. Available: https://www.researchgate.net/publication/281672818_Augmented_reality_enabled_iot_services_for_environmental_monitoring_utilising_serious_gaming_concept.