Implementation of Wireless Sensor Network (WSN) in Closed House Chicken Coops
Keywords:
Wireless Sensor Network, Closed House, ZigBee, Environmental Monitoring, Smart Poultry FarmAbstract
The development of Wireless Sensor Network (WSN) technology has opened up great opportunities for the application of automatic monitoring systems in various fields, including the modern livestock sector. In closed house chicken coop systems, temperature, humidity, and air quality control are crucial to ensuring livestock productivity and welfare. However, conventional systems that still rely on manual monitoring are often inefficient and prone to human error. This study aims to design and test the application of WSN in monitoring and controlling the environmental conditions of closed house chicken coops to create an efficient, adaptive, and sustainable monitoring system. The research was conducted experimentally by building a wireless sensor network using an Arduino microcontroller, ZigBee module, and DHT22 and MQ-135 sensors to measure temperature, humidity, and ammonia gas levels. The data was sent to a Raspberry Pi gateway and analyzed in real-time via a cloud server using the MQTT protocol. Test results showed that the system had a Packet Delivery Ratio (PDR) of 97.8%, an average latency of 1.24 seconds, and energy efficiency that increased by 15% after implementing sleep mode. Average temperature and humidity were successfully maintained within the optimal range of 28–32°C and 70–78%, while ammonia levels remained stable at around 21 ppm. The system is capable of automatically regulating ventilation and cooling based on actual environmental conditions. The application of WSN has been proven effective in improving operational efficiency, monitoring accuracy, and energy sustainability in closed house poultry houses. This study confirms the great potential of WSN as the foundation for smart poultry farms in the future, and further research is recommended to integrate machine learning algorithms for predictive analysis of livestock conditions.
Downloads
References
REFERENSI
[1] F. P. E. Putra, D. A. M. Putra, A. Firdaus, and ..., “Analisis kecepatan dan kinerja jaringan 5G (generasi ke 5) pada wilayah perkotaan,” … J. Informatics, 2023.
[2] F. P. E. Putra, F. Fauzan, S. Syirofi, M. Mursidi, D. Wahid, and A. Nuraini, “Sistem Pengendali Lingkungan Pertanian Dengan Wireless Sensor Network Untuk Mengoptimalkan Budidaya Hidroponik,” 2024. doi: 10.47709/digitech.v3i2.3461.
[3] F. P. E. Putra, K. Mufidah, R. M. Ilhamsyah, and ..., “Tinjauan performa RouterOS Mikrotik dalam jaringan internet: Analisis kinerja dan kelayakan,” Digit. …, 2023.
[4] F. P. E. Putra, D. E. Arissandi, A. Rofiqi, and M. F. Hidayat, “Pemanfaatan Mikrotik Dalam Manajemen Bandwidth Pada Jaringan Sekolah,” 2025, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Fauzan-Eka-Putra-2/publication/392420575_Pemanfaatan_Mikrotik_Dalam_Manajemen_Bandwidth_Pada_Jaringan_Sekolah/links/6848fab46b5a287c304a61ca/Pemanfaatan-Mikrotik-Dalam-Manajemen-Bandwidth-Pada-Jaringan-Sekolah.pdf
[5] A. Baidawi, “JARINGAN SENSOR NIRKABEL DAN IoT UNTUK KOTA PINTAR PAMEKASAN,” J. Sist. Inf. Kaputama, vol. 7, no. 2, pp. 104–110, 2023, doi: 10.59697/jsik.v7i2.108.
[6] F. P. E. Putra, M. Ghummah, M. Amrullah, and R. Hidayatullah, “Studi Kinerja Mesh Network untuk Penerapan Internet of Things (IoT) di Lingkungan Perkotaan,” 2025, researchgate.net.
[7] F. P. E. Putra, A. M. U. Solichin, and ..., “Pemanfaatan Teknologi Wireless dan Mobile Network Berbasis 5G Untuk Pemerataan Akses Jaringan di Indonesia,” Infotek J. …, 2025, [Online]. Available: https://e-journal.hamzanwadi.ac.id/index.php/infotek/article/view/30559
[8] N. Haidar Hari, F. P. Eka Putra, U. Hasanah, S. R. Sutarsih, and Riyan, “Transformasi Jaringan Telekomunikasi dengan Teknologi 5G: Tantangan, Potensi, dan Implikasi,” J. Inf. dan Teknol., pp. 146–150, 2023, doi: 10.37034/jidt.v5i2.357.
[9] F. P. E. Putra, Y. Setiawan, S. Arifin, and W. Hidayatullah, “Peran VPN dalam Menjaga Privasi Pengguna Jaringan Pub-lik,” 2025, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Fauzan-Eka-Putra-2/publication/392420576_Peran_VPN_dalam_Menjaga_Privasi_Pengguna_Jaringan_Publik/links/6848fa048a76251f22ecfd24/Peran-VPN-dalam-Menjaga-Privasi-Pengguna-Jaringan-Publik.pdf
[10] F. P. E. Putra, D. A. Siswoyo, M. I. A. Yaqin, and R. Oktavia, “Tinjauan Regulasi Siber dan Kebijakan Keamanan Jaringan 5G: Perspektif Nasional dan Internasional,” 2025, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Fauzan-Eka-Putra-2/publication/392411087_Tinjauan_Regulasi_Siber_dan_Kebijakan_Keamanan_Jaringan_5G_Perspektif_Nasional_dan_Internasional/links/6848f6a6df0e3f544f5e49d0/Tinjauan-Regulasi-Siber-dan-Kebijakan-Keamanan-Ja
[11] N. Saqib, N. F. Abdullah, A. Abu-Samah, H. A. H. Alobaidy, and R. Nordin, “Adaptive VNF Placement Considering Overall Latency and 5G Wireless Channel Reliability in Industry 4.0: A Reinforcement Learning Based Approach,” IEEE Access, vol. 12, pp. 88883–88896, 2024, doi: 10.1109/ACCESS.2024.3419065.
[12] B. P. Smyth, H. Khoshniyat, M. Barati, S. Clark, R. Mirzavand, and A. K. Iyer, “Energy Autonomous Dual-Band Antenna System for RFID-Based Real-Time Battery Level Monitoring,” IEEE Open J. Antennas Propag., vol. 5, no. 5, pp. 1140–1151, 2024, doi: 10.1109/OJAP.2024.3387331.
[13] A. Yinusa et al., “Machine Learning Approach to Nonlinear Fluid-Induced Vibration of Pronged Nanotubes in a Thermal–Magnetic Environment,” Vibration, vol. 8, no. 3, 2025, doi: 10.3390/vibration8030035.
[14] U. Shahid, M. Zunnurain Hussain, M. Hasan, A. Haider, J. Ali, and J. Altaf, “Hybrid Intrusion Detection System for RPL IoT Networks Using Machine Learning and Deep Learning,” IEEE Access, vol. 12, pp. 113099–113112, 2024, doi: 10.1109/ACCESS.2024.3442529.
[15] Y. R. Rivera-Julio, A. Pinto, R. Garcia, J. Aguilar Castro, and N. A. Pérez García, “Distributed Adaptive Coding Optimization for IoT Using Fulcrum Code and Model-Agnostic Meta-Learning (MAML) in Ultra-Low Latency Environments,” IEEE Access, vol. 13, pp. 139155–139172, 2025, doi: 10.1109/ACCESS.2025.3569165.
[16] X. Ning, H. Tian, Y. Lin, X. Yao, F. Hu, and Y. Yin, “Research on Multi-Objective Optimization Models for Intersection Crossing of Connected Autonomous Vehicles with Traffic Signals,” IEEE Access, vol. 12, pp. 36825–36840, 2024, doi: 10.1109/ACCESS.2024.3374041.
[17] H. Xu, H. Ma, and S. Zhou, “Influence of Potential Parameters on the Bistable Energy Harvester Under Random Excitation,” ASCE-ASME J. Risk Uncertain. Eng. Syst. Part B Mech. Eng., vol. 11, no. 4, 2025, doi: 10.1115/1.4068585.
[18] X. Qiu et al., “Joint Device Charging and Fresh Data Retrieval with Mobile Edge Device in Wireless-Powered IoT Systems,” IEEE Trans. Consum. Electron., vol. 70, no. 4, pp. 7385–7397, 2024, doi: 10.1109/TCE.2024.3419128.
[19] S. T. Ahmed, A. A. Ahmed, A. Annamalai, and M. F. Chouikha, “A Scalable and Energy-Efficient LoRaWAN-Based Geofencing System for Remote Monitoring of Vulnerable Communities,” IEEE Access, vol. 12, pp. 48540–48554, 2024, doi: 10.1109/ACCESS.2024.3383778.
[20] D. Chatzoulis, C. Chaikalis, A. Xenakis, D. Kosmanos, and K. E. Anagnostou, “Channel Coding QoS Analysis in 5G V2X Dynamic Propagation Models,” IEEE Access, vol. 13, pp. 80149–80173, 2025, doi: 10.1109/ACCESS.2025.3566607.
[21] A. A. Khan, R. Ghodhbani, A. Alsufyani, N. Alsufyani, and M. A. Mohamed, “Leveraging blockchain-integrated explainable artificial intelligence (XAI) for ethical and personalized healthcare decision-making: a framework for secure data sharing and enhanced patient trust,” J. Supercomput., vol. 81, no. 15, 2025, doi: 10.1007/s11227-025-07844-0.
[22] P. Fan, J. Han, Y. Zhang, C. Zhang, and Z. Zhu, “Energy harvesting from a fiber-constrained dielectric elastomer generator embedded into a novel floating wave energy harvester,” Smart Mater. Struct., vol. 33, no. 11, 2024, doi: 10.1088/1361-665X/ad7f34.
[23] Y. Huang et al., “Optimized design and performance evaluation of a flexible thermoelectric generator for Low-thermal heat waste energy harvesting,” Appl. Therm. Eng., vol. 264, 2025, doi: 10.1016/j.applthermaleng.2024.125225.
[24] M. Ghahramani, “Find It with A Pencil: An Efficient Approach for Vulnerability Detection in Authentication Protocols,” IEEE Trans. Inf. Forensics Secur., vol. 18, pp. 2005–2014, 2023, doi: 10.1109/TIFS.2023.3262125.
[25] N.-S. Pham, S. Shin, L. Xu, W. Shi, and T. Suh, “Cross-Filter Structured Pruning for Efficient Sparse CNN Acceleration,” IEEE Access, vol. 13, pp. 129461–129475, 2025, doi: 10.1109/ACCESS.2025.3587027.
[26] M. A. Aboulhassan, A. H. A. Abd El-Malek, A. M. Salhab, and S. A. Zummo, “Performance Analysis and Path-Planning for Self-Energized UAV-Assisted Relay Networks,” IEEE Trans. Aerosp. Electron. Syst., vol. 60, no. 1, pp. 907–917, 2024, doi: 10.1109/TAES.2023.3332588.
[27] Z. Deng, C. Tang, T. Li, and D. He, “A Distributed Ledger-Assisted Robust and Trusted Service Protocol for VANETs,” IEEE Internet Things J., vol. 11, no. 24, pp. 40559–40571, 2024, doi: 10.1109/JIOT.2024.3451303.
[28] M. Zeng and J. He, “Deployment Optimization of Roadside Unit With Failure Probability Based on Stochastic Mixed Traffic Equilibrium,” IEEE Trans. Intell. Transp. Syst., vol. 25, no. 7, pp. 7792–7804, 2024, doi: 10.1109/TITS.2024.3352015.
[29] T. Sathiyapriya and R. Sudhakar, “Design of Circularly Polarized Koch Snowflake Fractal Antenna With Schottky Band Diode Rectifiers for RF Energy Harvesting Applications,” Int. J. Commun. Syst., vol. 38, no. 5, 2025, doi: 10.1002/dac.6063.
[30] T. N. Nguyen et al., “On the Dilemma of Reliability or Security in Unmanned Aerial Vehicle Communications Assisted by Energy Harvesting Relaying,” IEEE J. Sel. Areas Commun., vol. 42, no. 1, pp. 52–67, 2024, doi: 10.1109/JSAC.2023.3322756.
[31] J. J. Pérez-Solano, A. Soriano-Asensi, S. Felici-Castell, and J. Segura-Garciá, “Improving the precision of time synchronization protocols in ultra-wideband networks estimating the time of flight of the radio signal,” Comput. Commun., vol. 223, pp. 44–54, 2024, doi: 10.1016/j.comcom.2024.05.006.
[32] C. L. Ng et al., “A Versatile and Wireless Multichannel Capacitive EMG Measurement System for Digital Healthcare,” IEEE Internet Things J., vol. 11, no. 11, pp. 20120–20137, 2024, doi: 10.1109/JIOT.2024.3370960.
[33] C. Lin, Y. Liu, and D. Shang, “ORSAS: An Output Row-Stationary Accelerator for Sparse Neural Networks,” IEEE Access, vol. 11, pp. 44123–44135, 2023, doi: 10.1109/ACCESS.2023.3272564.
[34] E. J. Majeed and A. J. Majeed, “Harvesting Human Energy to Power Head Torches Using a Thermoelectric Generator †,” Eng. Proc., vol. 70, no. 1, 2024, doi: 10.3390/engproc2024070030.
[35] D. K. Sah, S. Srivastava, R. Kumar, and T. Amgoth, “An energy efficient coverage aware algorithm in energy harvesting wireless sensor networks,” Wirel. Networks, vol. 29, no. 3, pp. 1175–1195, 2023, doi: 10.1007/s11276-022-03125-3.
[36] J. Moosmann, H. Muller, N. Zimmerman, G. Rutishauser, L. Benini, and M. Magno, “Flexible and Fully Quantized Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems,” IEEE Access, vol. 12, pp. 75093–75107, 2024, doi: 10.1109/ACCESS.2024.3404878.
[37] T. Ji, Q. Sun, K. Li, and Z. Duan, “Utilizing the Internet of Things and Big Data for Traffic Management: The Role of Physical Network Systems and Collaborative Signal Light Control,” IEEE Trans. Intell. Transp. Syst., vol. 26, no. 9, pp. 14077–14085, 2025, doi: 10.1109/TITS.2024.3519661.
[38] R. Song, P. Xu, S. Jia, and Y. Zhang, “Experimental investigation on hydrokinetic energy harvesting from flow-induced vibration of oscillators with rod-shaped attachments,” Ocean Eng., vol. 319, 2025, doi: 10.1016/j.oceaneng.2024.120250.
[39] V. Goutham and V. P. Harigovindan, “NOMA Based Cooperative Relaying Strategy for Underwater Acoustic Sensor Networks under Imperfect SIC and Imperfect CSI: A Comprehensive Analysis,” IEEE Access, vol. 9, pp. 32857–32872, 2021, doi: 10.1109/ACCESS.2021.3060784.
[40] T. Liu and C. Zhang, “Method for Distributed Node Metric Measurement in Wireless Sensor Networks Based on Multiple Attributes,” Int. J. High Speed Electron. Syst., vol. 34, no. 3, 2025, doi: 10.1142/S0129156424401189.
[41] A. Luo, B. Lossouarn, and A. Erturk, “The effects of shear deformation and rotary inertia on the electrical analogs of beams and plates for multimodal piezoelectric damping,” Int. J. Circuit Theory Appl., vol. 52, no. 6, pp. 2985–2998, 2024, doi: 10.1002/cta.3899.
[42] L. Anchidin, A. Lavric, P.-M. Mutescu, A. I. Petrariu, and V. Popa, “The Design and Development of a Microstrip Antenna for Internet of Things Applications,” Sensors, vol. 23, no. 3, 2023, doi: 10.3390/s23031062.
[43] L. Ding, A. Datta, and S. Sen, “Biophysical Modeling of Capacitive Electro-Quasistatic Human Body Powering,” IEEE Trans. Biomed. Eng., vol. 72, no. 9, pp. 2593–2608, 2025, doi: 10.1109/TBME.2025.3547738.
[44] Y. Li, B. Mukhopadhyay, J. Xu, and M.-S. Alouini, “Experimental Validation of Cooperative RSS-Based Localization With Unknown Transmit Power, Path Loss Exponent, and Precise Anchor Location,” IEEE Trans. Wirel. Commun., vol. 23, no. 11, pp. 16482–16497, 2024, doi: 10.1109/TWC.2024.3441643.
[45] F. Bagheri, J. Bonaldo, N. Güler, M. Rivera, P. Wheeler, and R. Lima, “Enhanced Sliding Mode Control for Dual MPPT Systems Integrated with Three-Level T-Type PV Inverters,” Energies, vol. 18, no. 13, 2025, doi: 10.3390/en18133344.
[46] S. B. N. Sreeja, G. Sundaram, M. Rivera, P. Wheeler, and R. E. P. Guzmán, “Reinforcement Q-Learning-Based Adaptive Encryption Model for Cyberthreat Mitigation in Wireless Sensor Networks,” Sensors, vol. 25, no. 7, 2025, doi: 10.3390/s25072056.
[47] H. D. Alkhaldi, “Study of physical aspects and hydrogen storage potential of X2LiBH6 (X = K, Rb); A DFT investigation,” J. Energy Storage, vol. 132, 2025, doi: 10.1016/j.est.2025.117890.
[48] X. Zhang, C. Li, D. Li, and S. Jiang, “Study on Operation Parameter Characteristics of Induction Filter Distribution Transformer in Low-Voltage Distribution Network,” IEEE Access, vol. 9, pp. 78764–78773, 2021, doi: 10.1109/ACCESS.2021.3083750.
[49] A. Dutta, L. M. Campoverde, M. Tropea, and F. De Rango, “A Comprehensive Review of Recent Developments in VANET for Traffic, Safety & Remote Monitoring Applications,” J. Netw. Syst. Manag., vol. 32, no. 4, 2024, doi: 10.1007/s10922-024-09853-5.
[50] M. Aljebreen, M. Obayya, H. Mahgoub, S. S. Alotaibi, A. Mohamed, and M. A. Hamza, “Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in Internet of Things Environment,” IEEE Access, vol. 12, pp. 258–267, 2024, doi: 10.1109/ACCESS.2023.3345803.
[51] T. M. Le, H. M. Tran, K. Wang, H. V Pham, and S. V. T. Dao, “An Internet-of-Things-Integrated Deep Learning Model for Fault Diagnosis in Industrial Rotating Machines,” IEEE Access, vol. 13, pp. 57266–57286, 2025, doi: 10.1109/ACCESS.2025.3553155.
[52] A. Ismail, M. G. Abdel-Moneim, A. S. Abdel-Khalik, R. A. Hamdy, and S. Ahmed, “Contactless Power Transfer to Shaft-Mounted Loads via Multiphase Induction Machine With Decoupled Torque and Rotor Power Control,” IEEE Trans. Ind. Electron., vol. 72, no. 8, pp. 7839–7849, 2025, doi: 10.1109/TIE.2025.3532729.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Maskana Ramadhani, Kevin Oktavia Pratama, Khairurrozi (Penulis)

This work is licensed under a Creative Commons Attribution 4.0 International License.








