International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Blog/Latest News Contact Us
10th percentile
Powered by  Scopus
Scopus coverage:
Nov 2018 to May 2020


IJSTR >> Volume 9 - Issue 8, August 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

The Development Of Smart Farming Technologies And Its Application In Malaysia

[Full Text]



Gabriel Wee Wei En, Haritharan Devanthran



Agricultural innovation, big data, cloud computing, information technology, internet of thing.



Smart farming is a development in the agriculture industry by integrating information and communication technologies (ICT) into agricultural production. New technologies such as the Internet of Things (IoT) and Cloud system are expected to enhance this development by introducing artificial intelligence and robots in farming. This paper aims to gain insight into the development of smart farming technologies based on worldwide scientific literatures and to explore the adoption of smart farming technologies in Malaysia from the perspectives of experienced farmers in this field. The research includes conducting meta-analysis to combine the results from worldwide journals on the development of smart farming technologies in Malaysia. The research on Smart Farming technology started from 1999 with ‘Precision Farming’, Soil Properties’ and ‘Sustainable Agriculture’ after the introduction of the Third National Agricultural Policy (NAP3) in 1998. ‘Internet of Things’ was identified as the most researched Smart Farming technology in Malaysia. The trend of the development of Smart Farming technology in Malaysia is pointing towards urban farming solutions and achieving sustainable agriculture.



[1] Abolfazli, S., Sanaei, Z., Tabassi, A., Rosen, S., Gani, A., & Khan, S. U. (2015). Cloud adoption in Malaysia: Trends, opportunities, and challenges. IEEE Cloud Computing, 2(1), 60-68.W.-K. Chen, Linear Networks and Systems. Belmont, Calif.: Wadsworth, pp. 123-135, 1993. (Book style)
[2] Aimrun, W., Amin, M. S. M., & Nouri, H. (2011). Paddy field zone characterization using apparent electrical conductivity for rice precision farming. International Journal of Agricultural Research, 6(1), 10-28.
[3] Aimrun, W., Amin, M. S. M., Ahmad, D., Hanafi, M. M., & Chan, C. S. (2007). Spatial variability of bulk soil electrical conductivity in a Malaysian paddy field: key to soil management. Paddy and Water Environment, 5(2), 113-121.
[4] Ali, F., & Amran, N. A. (2016). Development of an Egg Incubator using Raspberry Pi for precision farming. International Journal of Agriculture, Forestry and Plantation, 2(1), 462-469.
[5] Amin, M. S. M., Aimrun, W., Eltaib, S. M., & Chan, C. S. (2004). Spatial soil variability mapping using electrical conductivity sensor for precision farming of rice. International Journal of Engineering & Technology, 1(1), 47-57.
[6] Aziz, N., & Othman, F. (2013). Design and implementation of ubiquitous chicken farm management system using ios smart phone. Research Notes in Information Science (RNIS), 12, 150-154.
[7] Azlin, A. A. N., Mansor, H., Hashim, A. Z., & Gunawan, T. S. (2017, November). Development of modular smart farm system. In 2017 IEEE 4th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) (pp. 1-6). IEEE.
[8] Azmi, M. A. A. B. N. (2015). Mobile Web To Control Farming System (MFS) (Doctoral dissertation, University Malaysia Pahang).
[9] Baharudin, M. S. M., Ibrahim, R., Abdan, K., & Rashidi, A. (2018). Feasibility Of Green Commercial Vertical System For Climbing Food Plant In Urban Area. International Journal on Sustainable Tropical Design Research and Practice. 11(2), 12-16.
[10] Banhazi, T. M., Lehr, H., Black, J. L., Crabtree, H., Schofield, P., Tscharke, M., & Berckmans, D. (2012). Precision livestock farming: an international review of scientific and commercial aspects. International Journal of Agricultural and Biological Engineering, 5(3), 1-9.
[11] Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27-40.
[12] Braun, H. J., Atlin, G., & Payne, T. (2010). Multi-location testing as a tool to identify plant response to global climate change. Climate change and crop production, 1, 115-138.
[13] Chuah, Y. D., Lee, J. V., Tan, S. S., & Ng, C. K. (2019, June). Implementation of smart monitoring system in vertical farming. In IOP Conference Series: Earth and Environmental Science (Vol. 268, No. 1, p. 012083). IOP Publishing.
[14] Harun, A. N., Ahmad, R., & Mohamed, N. (2015, May). Plant growth optimization using variable intensity and Far Red LED treatment in indoor farming. In 2015 International Conference on Smart Sensors and Application (ICSSA) (pp. 92-97). IEEE.
[15] Ibrahim, A. R., Ibrahim, N. H. N., Harun, A. N., Kassim, M. R. M., Kamaruddin, S. E., & Witjaksono, G. (2018, July). Bird Counting and Climate Monitoring using LoRaWAN in Swiftlet Farming for IR4. 0 Applications. In 2018 2nd International Conference on Smart Sensors and Application (ICSSA) (pp. 33-37). IEEE.
[16] Ismail, W. I. W., & Razali, M. H. (2011). Gantry System for Urban Crop Production. Engineering e-Transaction (ISSN 1823-6379), 6(2), 76-80.
[17] Jhuria, M., Kumar, A., & Borse, R. (2013, December). Image processing for smart farming: Detection of disease and fruit grading. In 2013 IEEE Second International Conference on Image Information Processing (ICIIP-2013) (pp. 521-526). IEEE.
[18] Jindarat, S., & Wuttidittachotti, P. (2015, April). Smart farm monitoring using Raspberry Pi and Arduino. In 2015 International Conference on Computer, Communications, and Control Technology (I4CT) (pp. 284-288). IEEE.
[19] Kaewmard, N., & Saiyod, S. (2014, October). Sensor data collection and irrigation control on vegetable crop using smart phone and wireless sensor networks for smart farm. In 2014 IEEE Conference on Wireless Sensors (ICWiSE) (pp. 106-112). IEEE.
[20] Kushairi, A., Singh, R., & Ong-Abdullah, M. (2017). The oil palm industry in Malaysia: thriving with transformative technologies. J Oil Palm Res, 29(4), 431-9.
[21] Lee, T. S., Najim, M. M. M., & Aminul, M. H. (2004). Estimating evapotranspiration of irrigated rice at the West Coast of the Peninsular of Malaysia, Journal of Applied Irrigation Science, 39(1), 103-117.
[22] Lim, L. J., Sambas, H., Goh, N. C., Kawada, T., & JosephNg, P. S. (2017). ScareDuino: Smart-Farming with IoT. International Journal of Scientific Engineering and Technology, 6(6), 207-210.
[23] Mamodu, M. M. (2014). Web-geospatial Water Management Decision Support System for Tanjung Karang Rice Irrigation Scheme, Malaysia (Doctoral dissertation, Universiti Putra Malaysia).
[24] Mat, I., Kassim, M. R. M., Harun, A. N., & Yusoff, I. M. (2018, November). Smart Agriculture Using Internet of Things. In 2018 IEEE Conference on Open Systems (ICOS) (pp. 54-59). IEEE.
[25] Mohd, M. M., Amin, M. S. M., Kamal, M. R., Wayayok, A., Aziz, S. A., & Yazid, M. (2014). Application of web geospatial decision support system for Tanjung Karang rice precision irrigation water management. In International Conference on Agricultura, Food and Environmental Engineering (ICAFEE’2014), Kuala Lampur, Malaysia, Jan (pp. 15-16).
[26] Mustafa, F. H., Bagul, A. H. B. P., SENOO, S., & Shapawi, R. (2016). A Review of Smart Fish Farming Systems. J Aqua Eng Fish Res, 2(4), 193-200.
[27] Niwattanakul, S., Singthongchai, J., Naenudorn, E., & Wanapu, S. (2013, March). Using of Jaccard coefficient for keywords similarity. In Proceedings of the international multiconference of engineers and computer scientists 1(6), 380-384.
[28] Nouri, H., Amin, M. S. M., Razavi, S. J., Anuar, A. R., & Aimrun, W. (2009). Precision agriculture concept: distribution pattern of selected soil and crop characteristics influenced by fertigation. European Journal of Scientific Research, 32(2), 231-240.
[29] Othman, Z. (2012). Information and communication technology innovation as a tool for promoting sustainable agriculture: a case study of paddy farming in west Malaysia (Doctoral dissertation, University of Malaya).
[30] Pretty, J., & Bharucha, Z. P. (2014). Sustainable intensification in agricultural systems. Annals of botany, 114(8), 1571-1596.
[31] Shamshiri, R., Weltzien, C., Hameed, I. A., J Yule, I., E Grift, T., Balasundram, S. K., & Chowdhary, G. (2018). Research and development in agricultural robotics: A perspective of digital farming. International Journal of Agricultural and Biological Engineering, 11(4), 1-11.
[32] Rizman, Z. I., Hashim, F. R., Yassin, I. M., Zabidi, A., Zaman, F. K., & Yeap, K. H. (2018). Smart multi-application energy harvester using Arduino. Journal of Fundamental and Applied Sciences, 10(1S), 689-704.
[33] Ruiz-Garcia, L., Lunadei, L., Barreiro, P., & Robla, I. (2009). A review of wireless sensor technologies and applications in agriculture and food industry: state of the art and current trends. Sensors, 9(6), 4728-4750.
[34] Schwab, K. (2017). The fourth industrial revolution. Currency.
[35] Sebby, K. (2010). The Green Revolution of the 1960's and Its Impact on Small Farmers in India.
[36] Shiang-Yen, T., Osman, M. A., Lee, W. P., & Wei, L. H. (2012). Application of Information and Communication Technology in Paddy Farming: Toward Information-based Agriculture. International Journal of Advancements in Computing Technology, 4(20), 363-370.
[37] Syam, T., & Jusoff, K. (2000, July). Remote sensing (RS) and geographic information system (GIS) technology for field implementation in Malaysian agriculture. In Seminar on repositioning agriculture industry in the next millennium (pp. 13-14).
[38] Yang, K., & Meho, L. I. (2006). Citation analysis: a comparison of Google Scholar, Scopus, and Web of Science. Proceedings of the American Society for information science and technology, 43(1), 1-15.
[39] UN. (2017). World Population Prospects: The 2017 Revision: Key Findings and Advance Tables. United Nations Department of Economic and Social Affairs.