The Development of Water Pollution Detector Using Conductivity And Turbidity Principles

Water pollution has caused negative impacts on human health as humans depend solely on water for drinking, cooking, and cleaning. Even more worrying is that the number of polluted rivers seems to increase as time progresses. Due to no real-time monitoring device being implemented, the authorities are unaware of any given river's real-time conditions. Therefore, this research aims to control the water pollution issue by designing and developing a low-cost device that can detect water pollutants and notifies the authorities if abnormalities occur. In this work, various water pollution sources in Malaysia have been identified: biochemical oxygen demand, ammoniacal nitrogen, and suspended solids. The general performance of the proposed device is also evaluated and analyzed. Water quality data is collected by the sensors and is sent to an IoT platform called ThingSpeak through a Wi-Fi module to be visualized and displayed. When the pollution is detected, the website will alert local authorities for their prompt actions. From the experiment conducted, the developed conductivity sensor managed to give readings with 6.84% and 6.35% error compared to the sensor in a benchmark paper and the ready-made sensor, respectively. Besides, the turbidity sensor also managed to give accurate readings according to various types of solution. The success of this research would help to reduce river pollution and provide positive outcomes to the environment. ABSTRAK: Pencemaran air telah menyebabkan kesan negatif terhadap kesihatan manusia kerana kebergantungan mereka terhadap air untuk minum, memasak dan mencuci. Lebih membimbangkan adalah, jumlah sungai tercemar yang semakin meningkat seiring tahun-tahun yang berlalu. Oleh kerana tiada alat pemantauan masa nyata yang dilaksanakan, pihak berkuasa tidak menyedari keadaan semasa air sungai. Oleh itu, projek ini bertujuan bagi mengawal masalah pencemaran air dengan merancang dan menghasilkan alat kos rendah yang dapat mengesan pencemaran air dan memberitahu pihak berkuasa sekiranya berlaku bacaan yang tidak normal. Melalui kajian ini, pelbagai sumber pencemaran air di Malaysia telah dikenal pasti: permintaan oksigen biokimia, nitrogen amonia dan pepejal terampai. Prestasi umum alat ini juga dinilai dan dianalisis. Kualiti data air dikumpulkan oleh pengimbas dan maklumat dihantar ke platform IoT yang disebut ThingSpeak melalui modul Wi-Fi bagi tujuan tinjauan dan paparan. Apabila pencemaran dikesan, laman web tersebut akan memberi amaran kepada pihak berkuasa tempatan untuk tindakan segera. Melalui eksperimen yang dijalankan, pengimbas kekonduksian yang dihasilkan berjaya memberikan bacaan dengan ralat 6.84% dan 6.35% berbanding pengimbas yang terdapat di kertas penanda aras dan pengimbas siap pakai. Selain itu, pengimbas kekeruhan yang digunakan mampu memberikan bacaan yang tepat mengikut pelbagai jenis larutan. Projek ini diharap dapat membantu mengurangkan pencemaran sungai dan memberikan impak positif kepada alam sekitar.