Sensor Review, Volume 35, Issue 1, January 2015.
Purpose The tremendous development in the agriculture sector has increased the amount of contamination in natural water sources. Hence, the water is polluted and unsafe to drink. Therefore, there is a need to determine the contamination level in natural water resources. Design/methodology/approach Three types of sensor arrays, were suggested: parallel, star, and delta. The simulation of all types of sensor array was carried out to calculate the sensors’ impedance value, capacitance, and inductance during their operation, to determine the best sensor array. The contamination state was simulated by altering the electrical properties values of the environmental domain of the model, to represent water contamination. Findings The simulation results show that all types of sensor array are sensitive to conductivity, σ, and permittivity, ε (i.e. contaminated water). Furthermore, a set of experiments was conducted to determine the relationship between the sensor’s impedance and the water’s nitrate and sulphate contamination. The performance of the system was observed where the sensors were tested, with the addition of distilled water with different concentrations of potassium nitrate and potassium sulphate. The sensitivity of the developed sensors was evaluated and the best sensor was selected. Practical implications Based on the outcomes of the experiments, the star sensor array has the highest sensitivity and can be used to measure the nitrate and sulphate contaminations in the water. Originality/value The star sensor array presented in this paper has the potential to be used as a useful low-cost tool for water source monitoring.
Purpose The tremendous development in the agriculture sector has increased the amount of contamination in natural water sources. Hence, the water is polluted and unsafe to drink. Therefore, there is a need to determine the contamination level in natural water resources. Design/methodology/approach Three types of sensor arrays, were suggested: parallel, star, and delta. The simulation of all types of sensor array was carried out to calculate the sensors’ impedance value, capacitance, and inductance during their operation, to determine the best sensor array. The contamination state was simulated by altering the electrical properties values of the environmental domain of the model, to represent water contamination. Findings The simulation results show that all types of sensor array are sensitive to conductivity, σ, and permittivity, ε (i.e. contaminated water). Furthermore, a set of experiments was conducted to determine the relationship between the sensor’s impedance and the water’s nitrate and sulphate contamination. The performance of the system was observed where the sensors were tested, with the addition of distilled water with different concentrations of potassium nitrate and potassium sulphate. The sensitivity of the developed sensors was evaluated and the best sensor was selected. Practical implications Based on the outcomes of the experiments, the star sensor array has the highest sensitivity and can be used to measure the nitrate and sulphate contaminations in the water. Originality/value The star sensor array presented in this paper has the potential to be used as a useful low-cost tool for water source monitoring.
