DOI : https://doi.org/10.18517/ijaseit.14.5.20448

Development of Self-generated and LPWA-based Crop Growth Environment Monitoring and Bigdata Analysis System

Yeon-Jae Oh (1)
(1) Department of Computer Engineering, Artificial Intelligence Major, Suncheon National University, Suncheon-si, Republic of Korea
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How to cite (IJASEIT) :
Oh, Yeon-Jae. “Development of Self-Generated and LPWA-Based Crop Growth Environment Monitoring and Bigdata Analysis System”. International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 5, Oct. 2024, pp. 1701-7, doi:10.18517/ijaseit.14.5.20448.
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Smart farms are a technology that greatly helps improve the productivity and quality of crops and is being actively introduced into indoor environments such as greenhouses. Various sensors are installed in greenhouses to collect data, which AI analyzes to find the optimal crop growth environment. Various studies have been conducted to control this environment automatically. However, it has not yet been distributed to field-grown crops. The main reason is that, unlike indoor environments, it is tough to collect sensor data to monitor the growth environment of crops in open fields where weather conditions change significantly and the power supply is complex. Additionally, because various sensors are used, the data formats of the devices are different, making it difficult to process. This paper presents a field crop growth environment monitoring and big data analysis system. The proposed system first solves power supply and data communication problems using solar power generation and LPWA technology. Additionally, based on the oneM2M architecture, data from various sensors is transmitted to the server using standardized technology. The transmitted data is stored and managed on the server as big data and can be used to predict the production and quality of field-grown crops and take appropriate measures. The proposed system is expected to create an environment optimized for the growth of field crops and help prevent and manage diseases.

H. O. Choe and M.-H. Lee, “Artificial Intelligence-Based Fault Diagnosis and Prediction for Smart Farm Information and Communication Technology Equipment,” Agriculture, vol. 13, no. 11, p. 2124, Nov. 2023, doi: 10.3390/agriculture13112124.

K. Joo, H. M. Kim, and J. Hwang, “Consequences of Psychological Benefits in the Context of Eco-Friendly Indoor Smart Farm Restaurants: The Moderating Role of Curiosity,” Sustainability, vol. 15, no. 21, p. 15496, Oct. 2023, doi: 10.3390/su152115496.

N. Sirimorok, R. M. Paweroi, A. A. Arsyad, and M. Köppen, “Smart Farm Security by Combining IoT Sensor Network and Virtualized Mycelium Network,” Sensors, vol. 23, no. 21, p. 8689, Oct. 2023, doi:10.3390/s23218689.

R. Dhillon and Q. Moncur, “Small-Scale Farming: A Review of Challenges and Potential Opportunities Offered by Technological Advancements,” Sustainability, vol. 15, no. 21, p. 15478, Oct. 2023, doi: 10.3390/su152115478.

N. Bafdal and I. Ardiansah, “Application of Internet of Things in Smart Greenhouse Microclimate Management for Tomato Growth,” International Journal on Advanced Science, Engineering and Information Technology, vol. 11, no. 2, pp. 427–432, Apr. 2021, doi:10.18517/ijaseit.11.2.13638.

R. E. Putri, N. U. Lestari, Ifmalinda, F. Arlius, I. Putri, and A. Hasan, “Monitoring and Controlling System of Smart Mini Greenhouse Based on Internet of Things (IoT) for Spinach Plant (Amaranthus sp.),” International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 1, pp. 131–136, Feb. 2024, doi:10.18517/ijaseit.14.1.18408.

M. O. Ojo, I. Viola, M. Baratta, and S. Giordano, “Practical Experiences of a Smart Livestock Location Monitoring System Leveraging GNSS, LoRaWAN and Cloud Services,” Sensors, vol. 22, no. 1, p. 273, Dec. 2021, doi: 10.3390/s22010273.

W. Choi, Y.-S. Chang, Y. Jung, and J. Song, “Low-Power LoRa Signal-Based Outdoor Positioning Using Fingerprint Algorithm,” ISPRS International Journal of Geo-Information, vol. 7, no. 11, p. 440, Nov. 2018, doi: 10.3390/ijgi7110440.

K. A. Ogudo, D. Muwawa Jean Nestor, O. Ibrahim Khalaf, and H. Daei Kasmaei, “A Device Performance and Data Analytics Concept for Smartphones’ IoT Services and Machine-Type Communication in Cellular Networks,” Symmetry, vol. 11, no. 4, p. 593, Apr. 2019, doi:10.3390/sym11040593.

R. Choi, S. Lee, and S. Lee, “Reliability Improvement of LoRa with ARQ and Relay Node,” Symmetry, vol. 12, no. 4, p. 552, Apr. 2020, doi: 10.3390/sym12040552.

C.-H. Huang, B.-W. Chen, Y.-J. Lin, and J.-X. Zheng, “Smart Crop Growth Monitoring Based on System Adaptivity and Edge AI,” IEEE Access, vol. 10, pp. 64114–64125, 2022, doi:10.1109/access.2022.3183277.

S. Qazi, B. A. Khawaja, and Q. U. Farooq, “IoT-Equipped and AI-Enabled Next Generation Smart Agriculture: A Critical Review, Current Challenges and Future Trends,” IEEE Access, vol. 10, pp. 21219–21235, 2022, doi: 10.1109/access.2022.3152544.

D. Pal and S. Joshi, “AI, IoT and Robotics in Smart Farming: Current Applications and Future Potentials,” 2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS), pp. 1096–1101, Mar. 2023, doi:10.1109/icscds56580.2023.10105101.

K. Sathya Priya, J. Ancy Jenifer, S. P. Janani, M. Shilpa Aarthi, and T. Kavitha, “Crop Recommendation And Disease Prediction Using IOT And AI,” 2024 10th International Conference on Communication and Signal Processing (ICCSP), pp. 807–812, Apr. 2024, doi:10.1109/iccsp60870.2024.10543366.

L. Wang et al., “A Design for a Lithium-Ion Battery Pack Monitoring System Based on NB-IoT-ZigBee,” Electronics, vol. 12, no. 17, p. 3561, Aug. 2023, doi: 10.3390/electronics12173561.

H. Soy, “Coverage Analysis of LoRa and NB-IoT Technologies on LPWAN-based Agricultural Vehicle Tracking Application,” Sensors, vol. 23, pp. 8859, 2023, doi: 10.20944/preprints202308.2037.v1.

H. Nguyen, N. T. Le, N. C. Hoan, and Y. M. Jang, “Real-Time Mitigation of the Mobility Effect for IEEE 802.15.4g SUN MR-OFDM,” Applied Sciences, vol. 9, no. 16, p. 3289, Aug. 2019, doi: 10.3390/app9163289.

Semtech. “LoRa and LoRaWAN: A Technical Overview,” Online. 2019. [Online]. Available: https://lora-developers.semtech.com/uploads/documents/files/LoRa_and_LoRaWAN-A_Tech_Overview-Downloadable.pdf.

X. Yang, E. Karampatzakis, C. Doerr, and F. Kuipers, “Security Vulnerabilities in LoRaWAN,” 2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI), pp. 129–140, Apr. 2018, doi: 10.1109/iotdi.2018.00022.

R. Burczyk, A. Czapiewska, M. Gajewska, and S. Gajewski, “LTE and NB-IoT Performance Estimation Based on Indicators Measured by the Radio Module,” Electronics, vol. 11, no. 18, p. 2892, Sep. 2022, doi:10.3390/electronics11182892.

H. Fu, X. Wang, X. Zhang, A. Saleem, and G. Zheng, “Analysis of LTE-M Adjacent Channel Interference in Rail Transit,” Sensors, vol. 22, no. 10, p. 3876, May 2022, doi: 10.3390/s22103876.

A. Benouakta, T. M. Nguyen, F. Ferrero, L. Lizzi, and R. Staraj, “Design of a Multi-Standard UWB-LoRa Antenna Structure and Transceiver Board for High-Accuracy and Long-Range Localization Applications,” Electronics, vol. 12, no. 21, p. 4487, Oct. 2023, doi: 10.3390/electronics12214487.

M. Al mojamed, “LTM-LoRaWAN: A Multi-Hop Communication System for LoRaWAN,” Electronics, vol. 12, no. 20, p. 4225, Oct. 2023, doi: 10.3390/electronics12204225.

S. Ugwuanyi, G. Paul, and J. Irvine, “Survey of IoT for Developing Countries: Performance Analysis of LoRaWAN and Cellular NB-IoT Networks,” Electronics, vol. 10, no. 18, p. 2224, Sep. 2021, doi: 10.3390/electronics10182224.

oneM2M, “Published Specifications,” [Online]. Available: https://www.etsi.org/committee/1419-onem2m. Accessed on: Nov. 8, 2023.

M. Taştan and H. Gökozan, “Real-Time Monitoring of Indoor Air Quality with Internet of Things-Based E-Nose,” Applied Sciences, vol. 9, no. 16, p. 3435, Aug. 2019, doi: 10.3390/app9163435.

Y. M. Yusoff, R. Rosli, M. U. Karnaluddin, and M. Samad, “Towards smart street lighting system in Malaysia,” 2013 IEEE Symposium on Wireless Technology & Applications (ISWTA), pp. 301–305, Sep. 2013, doi: 10.1109/iswta.2013.6688792.

E. Kadusic, N. Zivic, C. Ruland, and N. Hadzajlic, “A Smart Parking Solution by Integrating NB-IoT Radio Communication Technology into the Core IoT Platform,” Future Internet, vol. 14, no. 8, p. 219, Jul. 2022, doi: 10.3390/fi14080219.

M. Pappalardo, A. Virdis, and E. Mingozzi, “An Edge-Based LWM2M Proxy for Device Management to Efficiently Support QoS-Aware IoT Services,” IoT, vol. 3, no. 1, pp. 169–190, Feb. 2022, doi: 10.3390/iot3010011.

oneM2M. “Published Specifications,” Release 3, [Online]. Available: https://www.onem2m.org/technical/published-specifications/release-3.

oneM2M. “Published Specifications,” Release 4, [Online]. Available: https://www.onem2m.org/technical/published-specifications/release-4.

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