In this paper, a low cost, real-time water quality monitoring system which can be applied in remote rivers, lakes, coastal areas and other water bodies is presented. The main hardware of the system consists of off-the-shelf electrochemical sensors, a microcontroller, a wireless communication system and the customized buoy. It detects water temperature, dissolved oxygen and pH in a pre-programmed time interval. The developed prototype disseminates the gathered information in graphical and tabular formats through a customized web-based portal and preregistered mobile phones to better serve relevant end-users. To check the system effectivity, the buoy's stability in harsh environmental conditions, system energy consumption, data transmission efficiency and webbased display of information were carefully evaluated. The experimental results prove that the system has great prospect and can be practically used for environmental monitoring by providing stakeholders with relevant and timely information for sound decision making.
This study implements remote sensing (RS) and geographic information system techniques in deriving physical and spectral characteristics of a catchment to aid in water quality monitoring. This approach is conducted by utilizing RS datasets like digital elevation model (DEM), satellite images, and on-site spectral measurements. A Shuttle Radar Topography Mission DEM was used for extracting physical profiles while Landsat Operational Land Imager was utilized to extract land cover information. This method was tested in a 22,000-ha catchment with dominant agricultural lands where large-scale mining companies are also operating actively. The land cover classification has an overall accuracy of 97.66%. Forest (50%) and cropland (32%) are the most dominant land cover within the catchment. The spectral signature of waters at designated sampling points was measured to evaluate its correlation to water quality data like pH and dissolved oxygen (DO). The correlation between the level of pH and reflectance implies a positive relationship (R 2 of 0.548) while that of DO and reflectance gives a negative correlation (R 2 of 0. 634). Results of this study demonstrate the practical advantage of exploiting remotely-sensed data in profiling and characterizing a catchment as it provides valuable information in understanding and mitigating contamination in an area. Through these RS-derived catchment profiles, insights on the contaminant's concentration and possible sources can be identified. The graphical and statistical analysis of the spectral data prove its potential in developing water quality models and maps.
Most developing countries depend on conventional water quality monitoring methods which are usually expensive, complicated, and time-consuming. In recent years, stationary and portable water quality monitoring and a mobile surface vehicle have increased the utilization of on-site water measurements and monitoring. The first has the disadvantage of small coverage area while the second has its cost and operational complexity. This paper addresses these issues by placing materials and equipment used in fixed online water quality monitoring and using a customized and low-cost unmanned surface vehicle. The measurements are taken automatically on the equipment onboard the unmanned surface vehicle (USV), transmitted wirelessly to a PC-based remote station or nearby stations and saved there in a dedicated database. The overall system comprises a commercial water quality sensor, a GSM and Zigbee module for a wireless communication system, a low-cost mobility platform, and the location/positioning system. During testing, all captured data like water quality parameters, location, and other essential parameters were collated, processed and stored in a database system. Relevant information from the USV can be viewed on a smartphone or a computer. The USV was also tested to conduct unmanned water quality measurements using the pre-inputted navigation route which shows a good result in navigation and data transmission. Water bodies with calm water such as lakes and rivers can use the USV, in a stand-alone mode or as a part of a networked sensor system.
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