IoT Based Water Quality Monitoring System By Using Zigbee Protocol

Haque, Halima; Labeeb, Kashshaf; Riha, Rabea Basri; Khan, Md. Nasfikur R.

doi:10.1109/esci50559.2021.9397031

Cited by 20 publications

(3 citation statements)

References 14 publications

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“…A microcontroller transmits sensor data to the Raspberry Pi through Zigbee, measuring pH, turbidity, conductivity, dissolved oxygen, and temperature. Sensor data is easily accessible because to cloud computing [29].…”

Section: Related Literaturementioning

confidence: 99%

Smart Aquaponics System for Oreochromis niloticus Production

Egnalig,

Jamero,

Tampong

et al. 2023

AIR

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Surigao City, found in the Northeastern part of Mindanao and facing the Pacific Ocean, boasts an abundance of fish; however, their prices are still high. This situation is due to the limited supply of freshwater fish, specifically Tilapia (Oreochromis niloticus), which is attributed to fishermen continuing to employ traditional fishpond methods. Considering this, the aim of this research is to design and develop a smart aquaponics system that incorporates recirculating aquaponics system (RAS) technology. The aim is to enhance the supply of Tilapia in the market. To achieve this, a developmental research design has been employed to create an efficient aquaponics system. The project incorporates two microcontrollers and multiple sensors to check essential parameters such as pH level, total dissolved solids, temperature, and water level. The study's results show a remarkable 6% fish growth, consistent operation of the system's circuit functions and water circulation, real-time data logging eased by the application software, and a power consumption of 193 watts. To examine the data acquired from the study, the researchers employed statistical methods such as mean, standard deviation, and frequency count. The tables and figures contain information on the system's hardware and software requirements, Tilapia growth characteristics, and a data overview of all sensor readings. The findings reveal that the smart aquaponics system could produce considerable growth of Tilapia within the tank while preserving fish development factors such as pH, salinity, total dissolved solids, temperature, and tank water level. The system likewise consumes less electricity and was rated "very acceptable" based on quantitative overall findings. These findings lead to the conclusion that Tilapia can effectively mass-produced using this aquaponics system. However, further research is necessary to prove a correlation between Tilapia grown in the smart aquaponics system and those raised through traditional fishpond methods.

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Section: Related Literaturementioning

confidence: 99%

Smart Aquaponics System for Oreochromis niloticus Production

Egnalig,

Jamero,

Tampong

et al. 2023

AIR

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“…Given the importance of understanding the variation of color with other water quality parameters, Yang [47] developed a multisensory system for measuring water quality parameters (temperature, dissolved oxygen content, pH value, ammonia nitrogen, and color) for fish farming through algorithmically optimized sensors, in which the measurement of color parameters in the water is sent in real-time via the ZigBee communication standard [48]. Further, Saravanan et al [49] also described a real-time IoT-based water quality monitoring system, which includes color as one of the parameters to be monitored in situ.…”

Section: Colormentioning

confidence: 99%

Advances in Technological Research for Online and In Situ Water Quality Monitoring—A Review

et al. 2022

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Monitoring water quality is an essential tool for the control of pollutants and pathogens that can cause damage to the environment and human health. However, water quality analysis is usually performed in laboratory environments, often with the use of high-cost equipment and qualified professionals. With the progress of nanotechnology and the advance in engineering materials, several studies have shown, in recent years, the development of technologies aimed at monitoring water quality, with the ability to reduce the costs of analysis and accelerate the achievement of results for management and decision-making. In this work, a review was carried out on several low-cost developed technologies and applied in situ for water quality monitoring. Thus, new alternative technologies for the main physical (color, temperature, and turbidity), chemical (chlorine, fluorine, phosphorus, metals, nitrogen, dissolved oxygen, pH, and oxidation–reduction potential), and biological (total coliforms, Escherichia coli, algae, and cyanobacteria) water quality parameters were described. It was observed that there has been an increase in the number of publications related to the topic in recent years, mainly since 2012, with 641 studies being published in 2021. The main new technologies developed are based on optical or electrochemical sensors, however, due to the recent development of these technologies, more robust analyses and evaluations in real conditions are essential to guarantee the precision and repeatability of the methods, especially when it is desirable to compare the values with government regulatory standards.

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“…The concept of IoT is helpful in a variety of application scenarios, including healthcare and wellness, home and building automation, increased energy efficiency [18], industrial automation, smart metering and smart grid infrastructures, asset management, and logistics, vehicular automation and smart transport, precision agriculture, smart shopping, aquaculture [19], and water quality assessment [20]. Owing to the advancement in the Internet of Things [21], many modern technologies are now utilising IoT [22] as a platform for monitoring and evaluating water quality [23]. Conclusively, with the help of cutting-edge ICT technology; The water quality has a significant impact on property values, and keeping the water quality in good condition would please people as well as benefit the aquatic ecosystems [24,25].…”

Section: Introductionmentioning

confidence: 99%

IoT-Based Water Monitoring Systems: A Systematic Review

Zulkifli

Garfan

Talal

et al. 2022

Water

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Water quality monitoring plays a significant part in the transition towards intelligent and smart agriculture and provides an easy transition to automated monitoring of crucial components of human daily needs as new technologies are continuously developed and adopted in agricultural and human daily life (water). For the monitoring and management of water quality, this effort, however, requires reliable models with accurate and thorough datasets. Analyzing water quality monitoring models by utilizing sensors that gather water properties during live experiments is possible due to the necessity for precision in modeling. To convey numerous conclusions regarding the concerns, issues, difficulties, and research gaps that have existed throughout the past five years (2018–2022), this review article thoroughly examines the water quality literature. To find trustworthy peer-reviewed publications, several digital databases were searched and examined, including IEEE Xplore®, ScienceDirect, Scopus, and Web of Science. Only 50 articles out of the 946 papers obtained, were used in the study of the water quality monitoring research area. There are more rules for article inclusion in the second stage of the filtration process. Utilizing a real-time data acquisition system, the criteria for inclusion for the second phase of filtration looked at the implementation of water quality monitoring and characterization procedures. Reviews and experimental studies comprised most of the articles, which were divided into three categories. To organize the literature into articles with similar types of experimental conditions, a taxonomy of the three literature was created. Topics for recommendations are also provided to facilitate and speed up the pace of advancement in this field of study. By conducting a thorough analysis of the earlier suggested methodologies, research gaps are made clear. The investigation largely pointed out the problems in the accuracy of the models, the development of data-gathering systems, and the types of data used in the proposed frameworks. Finally, by examining critical topics required for the development of this research area, research directions toward smart water quality are presented.

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IoT Based Water Quality Monitoring System By Using Zigbee Protocol

Cited by 20 publications

References 14 publications

Smart Aquaponics System for Oreochromis niloticus Production

Smart Aquaponics System for Oreochromis niloticus Production

Advances in Technological Research for Online and In Situ Water Quality Monitoring—A Review

IoT-Based Water Monitoring Systems: A Systematic Review

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