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ORIGINAL ARTICLE
APPLICATION OF INTERNET OF THINGS (IOT) FOR PHYSICOCHEMICAL PARAMETERS MEASUREMENT IN THE PVC AND BAMBOO MATERIAL
Mohd Radzi bin Rahman1, Saiful Iskandar Khalit1*, Ahmad Zaidi Hampden2
1Faculty of Bioresources and Food Industry, Universiti Sultan Zainal Abidin, Besut Campus, 22200 Besut, Terengganu, MALAYSIA
2Centre of Engineering Studies, School of Civil Engineering,Universiti Teknologi Mara, Kampus Samarahan, 94300 Kota Samarahan, Sarawak, MALAYSIA.
*Corresponding author: [email protected]
Received: 07/08/2023, Accepted: 24/08/2023, Available Online: 31/10/2023
Abstract
Aquaculture is the practice of cultivating and farming aquatic organisms under controlled conditions. High pH conditions, more toxic ammonia is present which can be harmful to aquatic organisms, particularly fish. The presence of ammonia in water can have implications for dissolved oxygen (DO) levels. The purpose of this study was to develop a real-time monitoring system using IoT for measurement pH, DO and ammonia-nitrogen via Blynk platform. Additionally, the study aimed to determine physicochemical parameters trend in aquaponic system using IoT application.
The reading of pH and DO from IoT sensor were collected from Blynk platform every ten seconds and ammonia nitrogen was observed twice a month. The presence of ammonia nitrogen in aquaponic system was determined using Nitrogen-ammonia reagent set, TNT, AmVer (Salicylate), High range. The data from this study were statistically analysed using Microsoft Excel 2019 to perform one-way ANOVA. This study's findings lead to the conclusion that there is a statistically significant relationship between internet accessibility and the intention to use Internet of Things (IoT) applications. Furthermore, the integration of IoT sensors in aquaponic systems has proven beneficial, offering advantages such as real-time monitoring, efficient resource management, and timely issue detection.
Keywords: Internet of things (IoT), physicochemical parameters, aquaponic system, Besut Campus, nitrogen-ammonia.
https://journal.unisza.edu.my/myjas
48 Introduction
Aquaculture refers to the farming or cultivation of aquatic organisms in controlled environments such as ponds, tanks, or ocean enclosures. Aquaculture plays a significant role in reducing pressure on wild fish stocks and supporting global food security. Aquaponics is a sustainable farming system that combines aquaculture and hydroponics and a new solution to the most critical problem in the world, food’s demand. According to Omer (2019), DO is the most important parameter in determining the water quality status and pH is the method to measure level of acidity and alkalinity that involves oxidation-reduction process. Aquaponic systems require monitoring of various physicochemical parameters to ensure optimal conditions for the fish and plants. Regular monitoring of these physicochemical parameters enables adjustments and interventions as needed to maintain optimal conditions in the aquaponic system.
Heavy metals refer to a group of metallic elements that have high atomic weights and densities. It's important to note that heavy metals are not inherently bad or harmful. Some heavy metals, such as iron (Fe), copper (Cu), and zinc (Zn), are essential micronutrients required by living organisms in small quantities. Heavy metal accumulation can have negative consequences for the organisms (APHA et al., 2017). Internet of things (IoT) are embedded with sensors, software and other technologies for the purpose of connecting and exchanging data with other devices. According to Zaini (2018), with a smartphone mobile application applied by using the Internet of Things (IoT), the farmer can monitor and control the level of ammonia, temperature, pH, DO, and nutrients. The mobile application is created with Blynk, which is an IoT platform for hardware control and data analysis.
In this final year project study, the location chosen to carry out this study is at block F3, Faculty of Bioresources and Food Industry, UniSZA Besut Campus. Various aquaponic material setups were placed outdoors in an experimental arrangement to establish an Internet of Things (IoT) system for monitoring pH, dissolved oxygen (DO), and ammonia-nitrogen (AN) levels. This was achieved through the utilization of the Blynk platform. Besides, the study is to determine physicochemical parameters trend in aquaponic system using IoT application. According to Kolding et al. (2008), the usage of Nile tilapia is due to the fish is common and can tolerate with variations types of salinity, water content and also temperature and also an aggressive fish that also could tolerate with to parasites and disease.
Materials and Methods Study Area
Besut campus lake was chosen as a study area due to its location that consists of many different types of potential pollutantsThe absence of prior research conducted in the specific area influenced our decision to select Besut Campus Lake as our study location. The Besut campus lake located at the coordinate of Latitude of 5°45’18.5” N and a Longitude of 102°37’34.7” E. It acts as a reservoir that functions to reduce the risks of floods during the monsoon season. The lake was subjected to the inflow of effluent from the entire campus, raising concerns about potential contamination with various elements.
This contamination could compromise the lake's suitability for recreational activities like kayaking and academic endeavors such as small-scale aquaculture. Additionally, rainwater might also contribute to non-point pollution as another potential water source. In this study, two sampling stations were selected. Sampling sites were named Station 1 (S1) and Station 2 (S2). As shown in Figure 1, S1 was located in the inlet area with Latitude 5°45’21.2” N and Longitude 102°37’38.8”
E. Besut campus lake consisted of several water inlets. The inlet chosen received effluent from a channel nearby connected to faculty and agriculture land at the backside of the faculty building.
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Meanwhile for S2, it is located at the outlet area with a Latitude of 5°45’16.1” N and a Longitude 102°37’30.6” E. Water from all over the lake will flow out through it. Besut campus lake has unique characteristics where during monsoon season, water from the lake will flow out to nearby streams but in the dry season, water from those streams will flow back into the lake. A tank was set as a control in the laboratory, known as Tank 1 (T1) to imitate the condition of a close water system in this study.
Figure 1. The study area which obtained from Google Earth map.
Aquaponic System Set Up and Operation
For this experiment, two tanks were arranged to accommodate different aquaponic systems. The primary material used for constructing these systems was polyethylene, which offers the advantage of being lighter and more manageable compared to steel or cement. The piping system consists of components responsible for water flow and those that hold the growing media, where pots and actual plants are positioned. These components are made from food-safe PVC and bamboo to ensure the well-being of fish and plants. Holes were drilled in the PVC and bamboo, with a gap of 15cm between each hole. To facilitate the water movement, a submersible pump (50Hz, 25W, 1800L/H) has been utilized to transfer water from the fish tank, lifting it out of the tank. The water then returns to the fish rearing tank via gravity, after flowing through the piping system and outflow pipe. To provide some shade, a sunshade netting with a shade factor of 90%
was cut into approximately 1.6 feet sections, and 20mm PVC pipes were cut and assembled to create stands for installation. This shading process continued until completion.
Fish Rearing Condition
Fifty adult tilapias were obtained from PPA Machang, located in Kelantan. Before the talapias released into a different tank, fish were acclimating for 20 minutes which are using different aquaponic materials. The fish were provided with a daily feed consisting of a commercial floating pellet, equivalent to 3.0% of their body mass.
50 Develop the IoT Application
The process of preparing the sensors took several weeks to complete for the research. The setup of the IoT sensor was successfully established, and the necessary coding was entered into the Hibiscus Sense ESP32. This choice allowed for a swift initiation of the IoT project, benefitting from the capabilities of the powerful and widely used dual-core ESP32 microcontroller. The accuracy of the IoT sensors, specifically for pH and dissolved oxygen (DO), was verified prior to their placement near the fish tanks. Furthermore, the functioning of the IoT sensors could be conveniently monitored using a mobile phone connected through the Blynk platform.
Sample Collection
In this research, measurements of dissolved oxygen (DO) and pH levels were monitored using a mobile phone interface provided by the Blynk platform. Data readings were captured at 10-second intervals, and the Blynk platform facilitated the graphical representation of DO and pH trends. The DO and pH sensors underwent daily monitoring to verify their operational status and connectivity.
The Aqua-DP data was gathered bi-daily—both in the morning and evening—spanning a duration of 20 days.
Ammoniacal Nitrogen
The concentration of ammoniacal nitrogen was determined using the salicylate method, also known as method 10023. The multiparameter portable colorimeter (DR900) was employed, with the procedure starting by selecting program 342 for ammonia LR TNT. To create the blank solution, 2.0 ml of distilled water was mixed with the diluent reagent. Similarly, the sample was prepared by combining 2.0 ml of the sample with the diluent reagent. Following this, each vial was loaded with an ammonia salicylate reagent powder and an ammonia cyanurate reagent powder using a funnel. The vials were then sealed tightly and vigorously shaken to dissolve the powder.
The reaction was initiated by starting the DR900 timer, set for a duration of 20 minutes. Once the timer elapsed, the blank vial underwent cleaning and was placed into the DR900's cell holder. The ZERO button was pressed until the display showed a reading of 0.00 mg/L. Subsequently, the sample vial was cleaned, inserted into the cell holder, and the READ button was pressed to obtain the measurement displayed in mg/L. In this study, the salicylate method or method 10023 was employed to determine the concentration of ammoniacal nitrogen. The multiparameter portable colorimeter (DR900) was utilized, starting with the initiation of program 342, ammonia LR TNT. To prepare the blank, 2.0 ml of distilled water was added to the diluent reagent. Similarly, the sample was prepared by adding 2.0 ml of the sample to the diluent reagent. Each vial was then equipped with one ammonia salicylate reagent powder and one ammonia cyanurate reagent powder using a funnel. The vials were tightly closed and vigorously shaken to dissolve the powder. The reaction was initiated by starting the timer on the DR900 for a duration of 20 minutes. Upon completion of the timer, the blank vial was cleaned and inserted into the cell holder of the DR900, with the ZERO button pressed until the display showed a reading of 0.00 mg/L. Subsequently, the sample vial was cleaned, inserted into the cell holder, and the READ button was pressed to obtain the results displayed in mg/L.
Results and Discussion
The first part of this chapter describes the observation for data sample of Dissolved Oxygen (DO) and Potential Hydrogen (pH) from mobile phone through Blynk platform. The second part of this chapter describe the observation for data sample of DO using Aqua-DP in the morning and
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evening for 20 days. The third part of this chapter describe the measurement for nitrogen-ammonia using nitrogen-ammonia reagent set.
Internet of Things (IoT) Application
Figure 2 shows graph from Blynk platform for twenty days. Blynk is a software platform that allows various hardware platforms such as RPi, Arduino, ESP8266, and others to connect to the Internet and be controlled through a mobile application. It provides the ability to display sensor measurements, store data in memory, and send notifications.
Figure 2. Graph from Blynk platform.
This experimental research used the application of IoT technology to measure and monitor pH and DO. The developed real time monitoring system can measure pH and DO at any time, and the data was recorded every ten seconds every day. The graph from Blynk platform shows different fluctuation between pH and DO level. The pH and DO data can be easily displayed on a smartphone using Blynk mobile application.
Physicochemical Parameter
Figure 3 illustrates the average pH and dissolved oxygen (DO) readings over a ten-day observation period. The outcomes reveal a diminishing trend in DO readings, attributed to a malfunction in the DO sensor, which encountered technical issues during this research.
Additionally, a weak internet connection contributed to the IoT sensor's offline status. The escalating temperature in Terengganu, peaking at 35°C, further compounded the situation.
Elevated water temperatures typically lead to reduced oxygen solubility. Meanwhile, the pH readings exhibited no notable differences from day 2 onward. For most aquaponic fish species, the optimal pH range lies between 6.8 and 7.4. Maintaining nutrient solutions in aquaponics proves more intricate compared to hydroponic solutions. This complexity arises from factors like fish feeding rate, hydraulic loading rate, and pH, all of which collectively influence the stability of the aquaponic solution, as stated by Chu et al. (2023).
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Figure 3. Reading of pH and DO (first 10 days)
Figure 4 shows the observation of average reading on pH and DO for the next ten days. Based on the result, it shows the reading of DO fluctuates due to the water quality for both tanks were in a good condition. Dissolved oxygen in an aquaponic system is significantly influenced by water quality, which is affected by many environmental factors (Ren et al., 2018). In addition, the reading of DO sensor was stable due to good internet connection. Next, the reading of pH shows no significant different from day 2 onwards. Several factors can contribute to high pH levels in an aquaponic system such as high alkalinity of source water, nitrification process, lack of carbon dioxide (CO2), reduced plant uptake of acidic compounds and insufficient organic matter breakdown.
Figure 4. Reading of pH and DO (next 10 days)
7.451
8.114 8.172 8.094 8.028 8.083 7.997 7.903 8.085 8.178
3.242
4.351
3.481
2.503
1.976
1.471
0.696
0.133 0.22 0.333
-1 0 1 2 3 4 5 6 7 8 9
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day 10 pH DO
8.217
7.906 7.75 7.884 7.872 8.063
7.539 7.409 7.851
7.557
0.315 0.823 0.809
2.597 2.534
1.821 1.743
0.287
1.452
2.178
0 1 2 3 4 5 6 7 8 9
Day 11 Day 12 Day 13 Day 14 Day 15 Day 16 Day 17 Day 18 Day 19 Day 20 pH DO
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Figure 5 depicts the recorded levels of dissolved oxygen (DO) during both morning and evening periods, spanning from day 1 to day 10, as measured by the Aqua-DP instrument. The outcome distinctly illustrates a noteworthy disparity in DO readings between the morning and evening timeframes. DO concentrations within an aquaponic system are subject to fluctuations influenced by multiple factors, including natural diurnal variations and plant respiration. The disparity in DO levels observed between the morning and evening periods can be influenced by diverse elements, such as system design, stocking density, plant biomass, aeration, temperature, and various environmental conditions.
Figure 5. Reading of DO using Aqua-DP instrument (first 10 days)
Figure 6 shows the reading of DO levels in the morning and evening for next ten days. The result shows the significant different on the graph of DO reading between morning and evening using Aqua-DP instrument. DO levels for tank A was higher than tank B in the morning than evening the reading of DO levels was decrease but tank A still higher thank tank B. Hence, the specific reason for the disparity in DO levels between morning and evening can differ depending on various circumstances. Photosynthesis, respiration and temperature also possible reasons for the difference. The DO levels for most fish species should be maintained above 5 mg/L (milligrams per liter) to ensure their well-being.
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
Dissolved Oxygen (DO), mg/L
Day
Tank A Tank B
Morning Afternoon
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Figure 6. Reading of DO using Aqua-DP instrument (next 10 days)
Ammoniacal Nitrogen (AN)
Figure 7 shows the results of ammoniacal nitrogen reagent test sample for tank A and tank B. The colour of ammoniacal nitrogen sample was changed due to high range of ammonia presence in the water between tank A and tank B.
Figure 7. Sample of ammoniacal nitrogen reagent test
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
11 12 13 14 15 16 17 18 19 20 11 12 13 14 15 16 17 18 19 20
Dissolved Oxygen (DO), mg/L
Day Tank A Tank B
Afternoon Morning
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Based on the data presented in Table 4.1, the outcomes obtained from the nitrogen-ammonia reagent set indicate that the nitrogen-ammonia concentration exceeded 2.5 mg/L for both tank A and tank B when employing the low range reagent set. In contrast, the utilization of the high range reagent set revealed a notably elevated nitrogen-ammonia content in the water samples from both tank A and tank B. This elevated presence of ammonia can be attributed to the accumulation of fish waste and other organic substances within the water.
The increased levels of ammonia within an aquaponic system can yield adverse consequences for both fish and plants. These ramifications include compromised fish health, impaired plant growth, and disruption of beneficial bacteria populations. It's noteworthy that heightened ammonia levels in water serve as an indicator of suboptimal water quality, emphasizing the importance of maintaining appropriate ammonia levels within the system.
Table 1. Result of ammoniacal nitrogen reagent test
Tank A Tank B
>2.5mg/L (low range) >2.5mg/L (low range) 3mg/L (high range) 5mg/L (high range)
Condition of Plant
Figure 8 portrays the status of plants subsequent to their relocation into the aquaponic system.
Within a week, the lettuce plants exhibited signs of wilting, attributed to various factors encompassing excessive watering, heat stress, and the phenomenon of transplant shock. The act of transplanting lettuce seedlings into a fresh growing medium can potentially trigger a period of transplant shock. However, the primary contributors to the wilting of lettuce plants were the dual factors of overwatering and heat stress.
Lettuce, being a crop favourable to cooler conditions, is particularly vulnerable to heat stress. This is especially pertinent considering the climate in Terengganu, where temperatures surged to 35 °C. Consequently, the leaves of the lettuce wilted and underwent dehydration.
Sustained exposure to elevated heat levels without adequate irrigation can lead to irrevocable damage and ultimately the demise of the plants.
Figure 8. Condition of plant wilt
56 Condition of Fish
Figure 9 illustrates the occurrence of tilapia mortality, attributed to a range of prevalent factors that can incite such outcomes. Tilapia fish are notably responsive to shifts in water quality. Adverse water conditions, encompassing elevated concentrations of ammonia, nitrites, or other pollutants, diminished levels of dissolved oxygen, heightened temperatures, or imbalanced pH levels, can collectively heighten stress levels among the fish population, ultimately culminating in disease or fatality.
Tilapias are also susceptible to an array of diseases and infections, spanning bacterial and parasitic afflictions. The influence of environmental factors further amplifies the potential for tilapia mortality, as extreme weather events and abrupt fluctuations in temperature can significantly impact their well-being and survival.
Figure 9. Condition of the dead fish
Conclusion
This study developed a real time monitoring of Internet of Things (IoT) for measurement pH, DO, and ammonia-nitrogen using the Blynk platform and to determine physicochemical parameters trend in aquaponic system using IoT application. the dissolved oxygen (DO) readings exhibited fluctuations, which can be attributed to the favourable water quality maintained in both tanks. The levels of dissolved oxygen in an aquaponic system are notably influenced by water quality, a factor determined by a multitude of environmental elements (Ren et al., 2018). Furthermore, the stability of the DO sensor readings can be attributed to the presence of a strong internet connection.
Conversely, the pH readings demonstrated no significant divergence from day 2 onwards.
Elevated pH levels within an aquaponic system can be attributed to various factors, including the high alkalinity of the source water, the nitrification process, insufficiency of carbon dioxide (CO2), reduced plant uptake of acidic compounds, and inadequate decomposition of organic matter. The utilization of IoT technology was employed to gauge and oversee pH and DO levels. The resultant real-time monitoring system facilitated the measurement of pH and DO at any given moment, with data being recorded at ten-second intervals daily. The graphical representation of these measurements, viewed through the Blynk platform, illustrated distinctive fluctuations in the pH and DO levels. The Blynk mobile application effortlessly exhibited the pH and DO data on a smartphone interface. IoT sensors provide continuous and real-time monitoring of crucial
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parameters such as water quality, temperature, pH levels, nutrient levels, dissolved oxygen, and fish behaviour. These data enables farmers to detect any deviations or abnormalities promptly and take corrective actions, minimizing the risk of crop failure or fish mortality.
Acknowledgements
Authors would like to thank to Faculty of Bioresources and Food Industry and Centre of Laboratory Management Centralized (CLMC) for their support and facility.
References
Alam, M. A.; Rahmat, N. A.; Mijin, S.; Rahman, M. S.; Hasan, M. (2022). Influence of palm oil mill effluent (POME) on growth and yield performance of Brazilian spinach (Alternanthera sissoo).
Journal of Agrobiotechnology, v. 13, n. 1, p. 40-49.
Ami, A. (2018). Analysis of Basic Physical-Chemical Parameters, Nutrients and Heavy Metals Content in Surface Water of Small Catchment Area of Karašica and Vuˇ cica Rivers in Croatia.
Angkha, B., Verma, A. K., Kumar, S. H., Prakash, C., & Thomas, R. M. (2020). Mobilization of mica by Bacillus sp. and its effect on Nile tilapia (Oreochromis niloticus) cum holy basil (Ocimum tenuiflorum)–based aquaponic system. Aquaculture International, 28(5), 2045- 2058.
APHA, AWWA, & WEF. (2017). 3120 B. Iductively Coupled Plasma (ICP) Method. Standard Methods for the Examination of Water and Wastewater, American Public Health Association, 23, 1–5.
Baßmann, B., Brenner, M., & Palm, H. W. (2017). Coupled Aquaponic System.
Bai, Chunguang; Dallasega, Patrick; Orzes, Guido; Sarkis, Joseph (1 November 2020). "Industry 4.0 technologies assessment: A sustainability perspective". International Journal of Production Economics. 229: 107776.
Chu, Y.-T.; Bao, Y.; Huang, J.-Y.; Kim, H.-J.; Brown, P.B. (2023). Supplemental C Addressed the PH Conundrum in Sustainable Marine Aquaponic Food Production Systems. 12, 69.
Dawood, M. A., Magouz, F. I., Mansour, M., Saleh, A. A., Asely, A. M. E., Fadl, S. E., ... & Al- Misned, F. (2020). Evaluation of yeast fermented poultry by-product meal in Nile Tilapia (Oreochromis niloticus) feed: Effects on growth performance, digestive enzymes activity, innate immunity, and antioxidant capacity. Frontiers in veterinary science, 6, 516.
Kolding, J., Haug, L., & Stefansson, S. (2008). Effect of ambient oxygen on growth and reproduction in Nile tilapia (Oreochromis niloticus). Canadian Journal of Fisheries and Aquatic Sciences, 65(7), 1413–1424.
Lin, K., Zhu, Y., Zhang, Y., & Lin, H. (2019). Determination of ammonia nitrogen in natural waters:
Recent advances and applications. Trends in Environmental Analytical Chemistry, 24, e00073.
58
Lind, C. E., Agyakwah, S. K., Attipoe, F. Y., Nugent, C., Crooijmans, R. P. M. A., & Toguyeni, A.
(2019). Genetic diversity of Nile tilapia (Oreochromis niloticus) throughout West Africa.
Scientific Reports, 9(1), 1–12.
Mamat, N. Z., Shaari, M. I., Amirul, N., & Abdul, A. (2016). The Production of Catfish and Vegetables in an Aquaponic System. 7(4), 5–7.
Omer, N. H. (2019). Water Quality Parameters. Water Quality - Science, Assessments and Policy, 18.
Rafiullah Khan, Sarmad Ullah Khan, Rifaqat Zaheer and Shahid Khan, (2017) ”Future Internet:
The Internet of Things Archi-tecture, Possible Applications and Key Challenges,” in Pro- ceedings of Frontiers of Information Technology (FIT), pp. 257-260.
Ren, Q., Zhang, L., Wei, Y., & Li, D. (2018). A method for predicting dissolved oxygen in aquaculture water in an aquaponics system. Computers and electronics in agriculture, 151, 384-391.
Robertson, G.P., Groffman, P.M., 2007. Nitrogen transformations. In: Paul, E.A. (Ed.), Soil Mi- crobiology, Biochemistry, and Ecology. Springer, New York, USA, pp. 341–364.
Sallenave, R. (2016). Important Water Quality Parameters in Aquaponics Systems. NM State University, 659–664.
Somayya Madakam, R. Ramaswamy, Siddharth Tripathi (2015) Internet of Things (IoT): A Literature Review.
Toensmeier, E. (2007). Perennial vegetables: from artichokes to zuiki taro. White River Junction:
Chelsea Green Publishing.
Yanes, A. R., Martinez, P., & Ahmad, R. (2020). Towards automated aquaponics: A review on monitoring, IoT, and smart systems. Journal of Cleaner Production, 263, 121571.
Yildiz, H. Y., Robaina, L., Pirhonen, J., Mente, E., Domínguez, D., & Parisi, G. (2017). Fish welfare in aquaponic systems: Its relation to water quality with an emphasis on feed and faeces-A review. Water (Switzerland), 9(1), 1–17.
Yuan, Y., Yuan, Y., Dai, Y., (2017). Economic Profitability of Tilapia Farming in China. pp.1253–
1264.
Zaini, A., Kurniawan, A., & Herdhiyanto, A-D, (2018) Internet of Things for Monitoring and Controlling Nutrient Film Technique (NFT) Aquaponic 2018 International Conference on Computer Engineering, Network and Intelligent Multimedia (CENIM) publisher by IEEE.
How to cite this paper:
Rahman, M. R., Khalit, S. I., Hampden, A. Z. (2023). Application of Internet of Things (IoT) for Physicochemical Parameters Measurement In The PVC And Bamboo Material. Malaysian Journal of Applied Sciences, 8(2), 47-58.
