(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Technology and Engineering Exploration (IJATEE)

ISSN (Print):2394-5443    ISSN (Online):2394-7454
Volume-10 Issue-109 December-2023
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Paper Title : Smart fertigation system with mobile application and fuzzy logic optimization
Author Name : Nurul Anis Zulaikha Izahar, Mohd Noor Derahman, Mohamad Afendee Mohamed and Imas Sukaesih Sitanggang
Abstract :

Precision farming plays a pivotal role in addressing the dual challenge of increasing crop productivity and reducing the environmental impact of agriculture. This arises from the critical need to elevate crop productivity to meet the increasing global demand for food, while actively confronting the economic and environmental consequences linked to suboptimal conventional farming practices. Conventional agriculture consistently grapples with inefficiencies in resource management, marked by the impractical and excessive utilization of fertilizers and water. This not only results in mounting production costs, but also gives rise to substantial threats to the environment, encompassing soil degradation, water pollution, and the loss of biodiversity. Thus, this study introduces a smart fertigation system, incorporating internet of things (IoT) technology and fuzzy logic optimization, specifically designed for large-scale bird's eye chili production. The innovative system integrates IoT technology with fuzzy logic to fine-tune fertilization and irrigation processes. Notably, a fuzzy inference system, implemented using MATLAB and Arduino UNO, dynamically optimizes nutrient delivery according to the growth stage of the chili plants. This sophisticated approach ensures that fertilization is precisely tailored to the specific needs of the crops at each developmental phase. Additionally, the development of the C-farm mobile application empowers farmers with remote monitoring capabilities, enabling them to oversee and manage the system from anywhere. This mobile application provides real-time insights into the smart fertigation system , granting farmers unprecedented control over their agricultural operations. Our findings also highlight the efficacy of fuzzy logic in enhancing the precision of automated fertigation systems. By dynamically adjusting nutrient delivery in response to the nuanced growth stages of chili plants, our system demonstrates its adaptability and responsiveness, resulting in optimized resource utilization and improved crop outcomes. This innovative integration of technology not only holds promise for large-scale crop production but also addresses the pressing issues of water and fertilizer waste in contemporary agriculture. Moving towards a more sustainable and efficient agricultural paradigm, the smart fertigation system, featuring fuzzy logic optimization and remote monitoring capabilities, stands as a beacon of progress in the quest for precision farming.

Keywords : Smart fertigation, Precision agriculture, Fuzzy logic, Arduino UNO, Birds eye chili.
Cite this article : Izahar NA, Derahman MN, Mohamed MA, Sitanggang IS. Smart fertigation system with mobile application and fuzzy logic optimization. International Journal of Advanced Technology and Engineering Exploration. 2023; 10(109):1580-1603. DOI:10.19101/IJATEE.2023.10102045.
References :
[1]Elferink M, Schierhorn F. Global demand for food is rising. Can we meet it. Harvard Business Review. 2016; 7(4):1-5.
[Google Scholar]
[2]Boopathy S, Anand KG, Priya ED, Sharmila A, Pasupathy SA. Iot based hydroponics based natural fertigation system for organic veggies cultivation. In third international conference on intelligent communication technologies and virtual mobile networks 2021 (pp. 404-9). IEEE.
[Crossref] [Google Scholar]
[3]Kummar L, Al-aani FS, Kahtan H, Darr M, Al-bashirl H. Data visualisation for smart farming using mobile application. International Journal of Computer Science and Network Security. 2019; 19:1-7.
[Google Scholar]
[4]Mathur B, Satapathy SM. An analytical comparison of mobile application development using agile methodologies. In international conference on trends in electronics and informatics 2019 (pp. 1147-52). IEEE.
[Crossref] [Google Scholar]
[5]Hakim IM, Singgih ML, Gunarta IK. Critical success factors for internet of things (IoT) Implementation in Automotive Companies, Indonesia. Sustainability. 2023; 15(4):1-18.
[Crossref] [Google Scholar]
[6]Duang-ek-anong S, Pibulcharoensit S, Phongsatha T. Technology readiness for internet of things (IoT) adoption in smart farming in Thailand. International Journal of Simulation: Systems, Science & Technology. 2019; 20:1-6.
[Crossref] [Google Scholar]
[7]En GWW, Devanthran H. The development of smart farming technologies and its application in Malaysia. International Journal of Scientific and Technology Research.2020; 9(8):561-66.
[8]Zaman NB, Raof WN, Saili AR, Aziz NN, Fatah FA, Vaiappuri SK. Adoption of smart farming technology among rice farmers. Journal of Advanced Research in Applied Sciences and Engineering Technology. 2023; 29(2):268-75.
[Crossref] [Google Scholar]
[9]Abidin SA, Ibrahim SN. Web-based monitoring of an automated fertigation system: an IoT application. In 12th Malaysia international conference on communications 2015 (pp. 1-5). IEEE.
[Crossref] [Google Scholar]
[10]Ahmed OM, Osman AA, Awadalkarim SD. A design of an automated fertigation system using IoT. In international conference on computer, control, electrical, and electronics engineering 2018 (pp. 1-5). IEEE.
[Crossref] [Google Scholar]
[11]Ruan J, Liao P, Dong C. The design and research on intelligent fertigation system. In international conference on intelligent human-machine systems and cybernetics 2015 (pp. 456-9). IEEE.
[Crossref] [Google Scholar]
[12]Joseph C, Thirunavuakkarasu I, Bhaskar A, Penujuru A. Automated fertigation system for efficient utilization of fertilizer and water. In international conference on information technology and electrical engineering 2017 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[13]Ahmad U, Alvino A, Marino S. Solar fertigation: a sustainable and smart IoT-based irrigation and fertilization system for efficient water and nutrient management. Agronomy. 2022; 12(5):1-24.
[Crossref] [Google Scholar]
[14]Zhang H, He L, Di GF, Choi D, Elia A, Heinemann P. LoRaWAN based internet of things (IoT) system for precision irrigation in plasticulture fresh-market tomato. Smart Agricultural Technology. 2022; 2:100053.
[Crossref] [Google Scholar]
[15]Khairodin FN, Rahman TA, Elijah O, Saharuddin HI. Smart IoT system for chili production using Lora technology. In integrated emerging methods of artificial intelligence & cloud computing 2021 (pp. 22-33). Cham: Springer International Publishing.
[Crossref] [Google Scholar]
[16]Rode S, Saraf R, Veigas J, Shetty N, Shardul S. Design and fabrication of IoT based agricultural automation system. In Biennial international conference on nascent technologies in engineering 2023 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[17]Zailani MZ, Jumaat SA. A monitoring system of soil moisture for fertigation system using IOT application. Evolution in Electrical and Electronic Engineering. 2021; 2(2):856-66.
[Google Scholar]
[18]Nandi PK, Mahmood MA. An automated irrigation and fertilization management system using fuzzy logic. In international conference on electrical information and communication technology 2021 (pp. 1-5). IEEE.
[Crossref] [Google Scholar]
[19]Jha K, Doshi A, Patel P, Shah M. A comprehensive review on automation in agriculture using artificial intelligence. Artificial Intelligence in Agriculture. 2019; 2:1-12.
[Crossref] [Google Scholar]
[20]Durai SK, Shamili MD. Smart farming using machine learning and deep learning techniques. Decision Analytics Journal. 2022; 3:100041.
[Crossref] [Google Scholar]
[21]Pezol NS, Adnan R, Tajjudin M. Design of an internet of things (IoT) based smart irrigation and fertilization system using fuzzy logic for chili plant. In international conference on automatic control and intelligent systems 2020 (pp. 69-73). IEEE.
[Crossref] [Google Scholar]
[22]Mohanraj I, Gokul V, Ezhilarasie R, Umamakeswari A. Intelligent drip irrigation and fertigation using wireless sensor networks. In technological innovations in ICT for agriculture and rural development 2017 (pp. 36-41). IEEE.
[Crossref] [Google Scholar]
[23]Saban M, Bekkour M, Amdaouch I, El GJ, Ait AB, Chaari MZ, et al. A smart agricultural system based on PLC and a cloud computing web application using LoRa and LoRaWan. Sensors. 2023; 23(5):1-16.
[Crossref] [Google Scholar]
[24]Pinatih PT, Dewi NN, Sutadarma IW. Green chili (Capsicum frutescens) ethanol extracts lowered triglyceride levels in rats fed with high-fat diet. Biomedicine. 2022; 42(6):1275-80.
[Crossref] [Google Scholar]
[25]Gupta C, Tewari VK, Machavaram R, Shrivastava P. An image processing approach for measurement of chili plant height and width under field conditions. Journal of the Saudi Society of Agricultural Sciences. 2022; 21(3):171-9.
[Crossref] [Google Scholar]
[26]Adek RT, Fikry M, Naluri H. Automatic control system using arduino UNO and web-based monitoring for watering Chili plants. Journal of Informatics and Telecommunication Engineering. 2022; 5(2):510-9.
[Crossref] [Google Scholar]
[27]Almasri AK. A proposed hybrid agile framework model for mobile applications development. International Journal of Software Engineering and Its Applications. 2016; 7(2):1-9.
[Google Scholar]
[28]Nazir M. Software quality assurance and android application development: a comparison among traditional and agile methodology. Lahore Garrison University Research Journal of Computer Science and Information Technology. 2020; 4(4):1-29.
[Crossref] [Google Scholar]
[29]Haidar R, Ibrahim K, Asaad R, Ahmad Z, Shamkuwar S. Building smart mobile apps with flutter and open AI AI-powered text and images and chatbots. Journal For Research in Applied Science and Engineering Technology. 2023; 11(6):904-8.
[Crossref]
[30]Rimal K, Shah KB, Jha AK. Advanced multi-class deep learning convolution neural network approach for insect pest classification using TensorFlow. International Journal of Environmental Science and Technology. 2023; 20(4):4003-16.
[Crossref] [Google Scholar]
[31]Bhagat SA, Dudhalkar SG, Kelapure PD, Kokare AS, Bachwani PS. Review on mobile application development based on flutter platform. International Journal for Research in Applied Science and Engineering Technology. 2022; 10(1):803-9.
[Google Scholar]
[32]Azry AS, Derahman MN, Mohamad ZA, Rahiman AR, Muzakkari BA, Mohamed MA. Fuzzy logic-based intelligent irrigation system with mobile application. Journal of Theoretical and Applied Information Technology. 2022; 100(18):5323-34.
[Google Scholar]
[33]Manan A, Wiley V, Lucas T. Programmer selection using modified fuzzy mamdani method. Lontar Komputer : Jurnal Ilmiah Teknologi Informasi. 2019; 10(2):108-18.
[Google Scholar]
[34]Wawan W, Zuniati M, Setiawan A. Optimization of national rice production with fuzzy logic using Mamdani method. Journal of Multidisciplinary Applied Natural Science. 2021:1-8.
[Crossref] [Google Scholar]
[35]Awalludin N, Gerhana YA, Mulyana E, Lukman N, Dauni P, Dzikrayah F. Implementation of fuzzy logic method to measure soil moisture and environmental temperature in automatic watering system based on internet of things. In 8th international conference on wireless and telematics 2022 (pp. 1-5). IEEE.
[Crossref] [Google Scholar]
[36]Sivanandam SN, Sumathi S, Deepa SN. Introduction to fuzzy logic using MATLAB. 2007; Springer.
[Crossref] [Google Scholar]
[37]Sharma S, Obaid AJ. Mathematical modelling, analysis and design of fuzzy logic controller for the control of ventilation systems using MATLAB fuzzy logic toolbox. Journal of Interdisciplinary Mathematics. 2020; 23(4):843-9.
[Crossref] [Google Scholar]
[38]Pierre NJ, Sefu B, Venuste S, D’amour MJ, Daniel K, Pierre NJ, et al. Smart crops irrigation system with low energy consumption. Journal of Appropriate Technology. 2023; 9(1):9-19.
[Crossref] [Google Scholar]
[39]Sukarsa I, Antara IK, Buana PW, Bayupati I, Wisswani NW, Puteri DW. Data storage model in low-cost mobile applications. Indonesian Journal of Electrical Engineering and Computer Science. 2022; 28(2):1-11.
[Google Scholar]