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Sains Malaysiana 54(8)(2025): 1945-1956
http://doi.org/10.17576/jsm-2025-5408-06
Pembangunan Parameter Pengesanan Bahan
Pencemar dan Aplikasi Pemberitahuan melalui Kemudahan Internet Perkara (IoT) untuk
Sensor Elektrokimia Mikrob
(Development of Pollutant Detection Parameters
and Notification Applications through Internet of Things (IoT) Facilities for
Microbial Electrochemical Sensors)
1Fuel Cell Institute, Universiti Kebangsaan Malaysia,
43600 UKM Bangi, Selangor, Malaysia
2Department of Chemical and Process Engineering, Faculty
of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM
Bangi, Selangor, Malaysia
3National Nanotechnology Center (NNC), Ministry of
Science, Technology, and Innovation (MOSTI), Precint 1, 62000, Putrajaya,
Malaysia
4Indah Water Research Centre (IWRC), Indah Water
Konsortium Sdn. Bhd. Lot 3938, Jalan Chan Chin Mooi, Titiwangsa, 53200 Kuala
Lumpur, Malaysia
Diserahkan: 26 November 2024/Diterima: 23 Jun 2025
Abstrak
Penyelidikan
ini memfokuskan pada pembangunan dan pengesahan biosensor untuk pemantauan
kualiti air yang cekap melalui pengesanan automatik isyarat ketidakpatuhan.
Biosensor ini menggunakan sistem elektrokimia mikrob yang maju dengan sokongan
PicoLog Cloud, yang mengumpul data, menganalisis trend dan menghantar pemberitahuan
kepada pengguna melalui SMS atau emel sekiranya terdapat ketidakpatuhan. Model
matematik telah dibangunkan untuk meningkatkan ketepatan pengesanan dengan
mengenal pasti Kadar Perubahan (RoC) isyarat biosensor sebagai parameter utama.
Model ini menetapkan ambang ±30 mA/min yang telah disahkan melalui uji kaji
makmal terkawal. Sensitiviti biosensor ini dapat dibuktikan melalui pengesanan
output arus elektrik (50-300 µA) dengan penurunan ketara pada 0 µA pada
kepekatan 100 mg/L 4-nitrofenol. Sistem ini berjaya mengesan lonjakan
isyarat yang ketara akibat pengenalan medium baharu dan membezakannya daripada
gangguan persekitaran seperti gangguan elektrik atau gelembung udara
terperangkap. Analisis komuniti mikrob menunjukkan kelimpahan dominan Proteobacteria (34%), khususnya Alphaproteobacteria dan Gammaproteobacteria yang menyokong
keadaan anaerobik yang diperlukan oleh Desulfobacterota (kurang daripada 10%). Walaupun kelimpahannya lebih rendah, Desulfobacterota memainkan peranan
penting dalam penjanaan arus, menonjolkan hubungan simbiotik antara spesies
mikrob untuk mengekalkan fungsi dan kecekapan biosensor. Penemuan ini
menegaskan kemampuan biosensor untuk menyediakan pemantauan masa nyata dan
pengesanan awal, mengurangkan kebergantungan pada pensampelan dan analisis
manual. Inovasi ini menawarkan penyelesaian mampan untuk loji rawatan air sisa
dan aplikasi pemantauan alam sekitar. Integrasi model matematik dengan
pemahaman mikrob meningkatkan kemampuan biosensor, membolehkan interpretasi
isyarat yang tepat dan operasi yang boleh dipercayai. Kajian ini membuktikan
potensi gabungan elektrokimia mikrob dan sistem awan automatik untuk penyelesaian
pemantauan kualiti air yang berskala dan berimpak tinggi.
Kata kunci: Biosensor
elektrokimia mikrob; model matematik; pemantauan kualiti air; pengesanan masa
nyata; sistem pemberitahuan automatik
Abstract
This study
focuses on developing and validating a biosensor for efficient water quality
monitoring through automatic detection of non-compliance signals. The biosensor
employs an advanced microbial electrochemical system supported by PicoLog
Cloud, which collects data, analyzes trends, and sends notifications to users
via SMS or email in the event of non-compliance. A mathematical model was
developed to enhance detection accuracy, identifying the Rate of Change (RoC)
of the biosensor signal as a key parameter. The model defines a threshold of
±30 mA/min, validated through controlled laboratory experiments. The
biosensor’s sensitivity was confirmed by the detection of current outputs
(50-300 µA), with significant drop to 0 µA at 100 mg/L of 4-nitrophenol. The
system successfully detected significant signal spikes caused by the
introduction of new media and differentiated these from environmental noise,
such as electrical interference or trapped air bubbles. Microbial community
analysis showed a dominant abundance of Proteobacteria (34%), particularly Alphaproteobacteria and Gammaproteobacteria, which
support anaerobic conditions required by Desulfobacterota (under 10%). Despite their lower abundance, Desulfobacterota play a critical role in current generation, highlighting a symbiotic
relationship between microbial species to maintain biosensor functionality and
efficiency. The findings underscore the biosensor’s ability to provide
real-time monitoring and early-warning detection, reducing reliance on manual
sampling and analysis. This innovation offers a sustainable solution for
wastewater treatment plants and environmental monitoring applications. The
integration of mathematical modeling with microbial insights strengthens the
biosensor’s capabilities, enabling precise signal interpretation and reliable
operation. This work demonstrates the potential of combining microbial
electrochemistry and automated cloud systems for scalable and impactful water
quality monitoring solutions.
Keywords: Automated notification system; mathematical
model; microbial electrochemical sensor; real-time detection; water quality
monitoring
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*Pengarang untuk surat-menyurat; email: limss@ukm.edu.my
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