A Concept Paper on Smart River Monitoring System for Sustainability in River

River is a major source of water in Malaysia and one of the major threats to its sustainability is pollution. The existing methods for monitoring of water quality in rivers are manual monitoring and continuous monitoring. These methods are costly and less efficient. Hence, we propose a smart river monitoring system (SRMS) that uses unmanned aerial vehicles (UAVs) or drones and low power wide area (LPWA) communication technology. The Internet of Things (IoT) and data analytic are promising techniques which provide real-time monitoring and enhances efficiency. However, due to the span of river that needs to be monitored, conventional communication technology such as Wi-Fi, Zigbee, Bluetooth are not suitable. Hence, there is the need for LPWA communication technology. We discuss the application of LPWA and UAV for sustainability of rivers in Malaysia as a case study. Preliminary results show that the use of UAV will increase the efficiency of measuring the water quality parameters compared to manual monitoring method. Also, real-time monitoring enables us to study the changes in water quality. Finally, we provide future direction in the application of UAV and LPWA for sustainability in river

Development, manufacture and application of a solid-state pH sensor using ruthenium oxide

The measurement of pH is undertaken frequently in numerous settings for many applications. The common glass pH probe is almost ideal for measuring pH, and as such, it is used almost ubiquitously. However, glass is not ideal for all applications due to its relatively large size, fragility, need for recalibration and wet-storage. Therefore, much research has been undertaken on the use of metal oxides as an alternative for the measurement of pH. Here, a solid-state potentiometric pH sensor is developed using ruthenium metal oxide (RuO2). Initially, pH sensitive RuO2 electrodes were prepared by deposition with radio frequency magnetron sputtering (RFMS) in a reactive oxygen plasma, onto screen-printed carbon based electrical contacts (substrates). These electrodes performed well, between pH 4 and 10, exhibiting Nernstian pH sensitivity, low hysteresis and low drift rate. However, these electrode were found to exhibit less than ideal properties outside this range (pH 2-12), though this could be overcome using a pH 12 conditioning protocol. Later, improved RuO2 pH sensitive electrodes were developed and characterised. Elimination of the carbon substrate material resulted in electrodes that displayed excellent performance from pH 2 to 12, even without pH 12 conditioning. Whilst this RuO2 electrode displayed excellent pH sensing performance, RuO2 along with all other metal oxide based pH sensors suffer from interference caused by strong oxidising and reducing agents. To reduce this interference, Ta2O5 and Nafion protective layers were studied. Using a combination of sputter deposited Ta2O5 (80 nm) and thermally cured drop-cast Nafion, an electrode was manufactured, which was immune to interference from dissolved oxygen, and resistant to stronger redox species. This electrode was found to outperform an unprotected RuO2 electrode and was suitable for application in several common beverage samples. In order to construct a potentiometric pH sensor a reference electrode is also required. Here, a pH insensitive reference electrode was developed by modification of the pH sensitive RuO2 electrode with a porous polymer junction containing SiO2. The reference electrode showed very low sensitivity to pH and KCl. The reference electrode provided a suitably stable potential over short periods of time, allowing accurate pH measurements to be made. The potential of the reference electrode was found to drift over longer time periods, however, this could be accounted for by recalibration. The developed working and reference electrodes were then used to construct a pH sensor. The sensor displayed excellent performance between pH 2 and 6; close to Nernstian sensitivity (-55.3 mV/pH), linear response (R2=1.0000) and excellent reproducibility (hysteresismV). The sensor was applied to several beverage samples, where it was shown to perform accurately, results within ±0.08 pH of a commercial glass pH sensor. The sensor develop here would be suitable for development into handheld and in-situ type pH sensor devices

Fabrication of a Miniature Multi-Parameter Sensor Chip for Water Quality Assessment

Water contamination is a main inducement of human diseases. It is an important step to monitor the water quality in the water distribution system. Due to the features of large size, high cost, and complicated structure of traditional water determination sensors and devices, it is difficult to realize real-time water monitoring on a large scale. In this paper, we present a multi-parameter sensor chip, which is miniature, low-cost, and robust, to detect the pH, conductivity, and temperature of water simultaneously. The sensor chip was fabricated using micro-electro-mechanical system (MEMS) techniques. Iridium oxide film was electrodeposited as the pH-sensing material. The atomic ratio of Ir(III) to Ir(IV) is about 1.38 according to the X-ray photoelectron spectroscopy (XPS) analysis. The pH sensing electrode showed super-Nernstian response (−67.60 mV/pH) and good linearity (R2 = 0.9997), in the range of pH 2.22 to pH 11.81. KCl-agar and epoxy were used as the electrolyte layer and liquid junction for the solid-state reference electrode, respectively, and its potential stability in deionized water was 56 h. The conductivity cell exhibited a linear determination range from 21.43 μ S / cm to 1.99 mS / cm , and the electrode constant was 1.566 cm−1. Sensitivity of the temperature sensor was 5.46 Ω / ° C . The results indicate that the developed sensor chip has potential application in water quality measurements

New Directions in Impedance Spectroscopy for High Accuracy, Augmented Information Extraction and Low Power Implementation

This thesis provides new directions in the impedance spectroscopy, making it an interesting investigation technique for emerging smart sensors. Modern technologies increasingly require sensors capable of giving accurate measurements extracted among a lot of undesired surrounding information while maintaining low power consumptions. In this scenario, the main focuses of this thesis are: 1) developing an accurate complex impedance system, 2) extracting the augmented information using multivariate statistical analysis and 3) implementing IS-based systems with low power consumptions. The first project shows the design of a miniaturized, low power and accurate vector analyser for multi-parameter measurements in real-time. It is a versatile platform well-suited to be interfaced with various impedance-based sensors. The vector analyser, based on an accurate application specific integrated circuit and a digital interface, has been statistically characterized in order to evaluate accuracy and resolution. The validation of the entire system was performing on two real-time biomedical applications. The second project concerns the combination of powerful statistical methods inside moisture content sensors. The multivariate statistical approaches boost the prediction capability of the sensors exploiting the impedance mismatch between a transmitting and reflecting excitation on a soil. Two probe systems have been manufactured and associated with linear and non-linear models for being tested on three soil types. The third project shows a low-power implementation of an impedance sensor based on a digital random excitation. The entire system is almost digital, made up by an ultra-low power platform with the aim to become a wearable device. In future developments, these new investigated directions can be simultaneously applied in the design of IS based sensors which extract the desired information with high accuracy and reduced power budget. The potential of such improved system can be employed in a lot of smart sensors, involving electrochemical, environmental, food, biological applications and wearable devices

Energy Optimization of Smart Water Systems using UAV Enabled Zero-Power Wireless Communication Networks

Real-time energy consumption is a crucial consideration when assessing the effectiveness and efficiency of communication using energy hungry devices. Utilizing new technologies such as UAV-enabled wireless powered communication networks (WPCN) and 3D beamforming, and then a combination of static and dynamic optimization methodologies are combined to improve energy usage in water distribution systems (WDS). A proposed static optimization technique termed the Dome packing method and dynamic optimization methods such as extremum seeking are employed to generate optimum placement and trajectories of the UAV with respect to the ground nodes (GN) in a WDS. In this thesis, a wireless communication network powered by a UAV serves as a hybrid access point to manage many GNsin WDS. The GNs are water quality sensors that collect radio frequency (RF) energy from the RF signals delivered by the UAV and utilise this energy to relay information via an uplink. Optimum strategies are demonstrated to efficiently handle this process as part of a zero-power system: removing the need for manual battery charging of devices, while at the same time optimizing energy and data transfer over WPCN. Since static optimization does not account for the UAV's dynamics, dynamic optimization techniques are also necessary. By developing an efficient trajectory, the suggested technique also reduces the overall flying duration and, therefore, the UAV's energy consumption. This combination of techniques also drastically reduces the complexity and calculation overhead of purely high order static optimizations. To test and validate the efficacy of the extremum seeking implementation, comparison with the optimal sliding mode technique is also undertaken. These approaches are applied to ten distinct case studies by randomly relocating the GNs to various positions. The findings from a random sample of four of these is presented, which reveal that the proposed strategy reduces the UAV's energy usage significantly by about 16 percent compared to existing methods. The (hybrid) static and dynamic zero-power optimization strategies demonstrated here are readily extendable to the control of water quality and pollution in natural freshwater resources and this will be discussed at the end of this thesis

Fabrication of a Miniature Multi-Parameter Sensor Chip for Water Quality Assessment

Water contamination is a main inducement of human diseases. It is an important step to monitor the water quality in the water distribution system. Due to the features of large size, high cost, and complicated structure of traditional water determination sensors and devices, it is difficult to realize real-time water monitoring on a large scale. In this paper, we present a multi-parameter sensor chip, which is miniature, low-cost, and robust, to detect the pH, conductivity, and temperature of water simultaneously. The sensor chip was fabricated using micro-electro-mechanical system (MEMS) techniques. Iridium oxide film was electrodeposited as the pH-sensing material. The atomic ratio of Ir(III) to Ir(IV) is about 1.38 according to the X-ray photoelectron spectroscopy (XPS) analysis. The pH sensing electrode showed super-Nernstian response (−67.60 mV/pH) and good linearity (R2 = 0.9997), in the range of pH 2.22 to pH 11.81. KCl-agar and epoxy were used as the electrolyte layer and liquid junction for the solid-state reference electrode, respectively, and its potential stability in deionized water was 56 h. The conductivity cell exhibited a linear determination range from 21.43 μ S / cm to 1.99 mS / cm , and the electrode constant was 1.566 cm−1. Sensitivity of the temperature sensor was 5.46 Ω / ° C . The results indicate that the developed sensor chip has potential application in water quality measurements

Imaging Microphysiometry of 2D and 3D Tissue Models: Method Development and Application

This thesis was focused on monitoring two essential parameters of life in cell and tissue culture: oxygen and pH. Oxygen tension and pH are two fundamental indicators for metabolic activity and they allow discriminating between normal and cancerous tissue. The parameters were analyzed on the one hand by using analyte-sensitive, planar sensor foils detecting changes in the microenvironment of cells and on the other hand by applying different extracellular pH values to see how cells reacted in different developmental stages or phenotypes. Four different cell lines were analyzed: (i) NRK cells representing normal cells, (ii) A549 cells which are human lung cancer cells and (iii) SK-MEL-28 and SpiCa cells which are two human skin cancer subtypes. Initial methodological investigations demonstrated the high spatial resolution of the oxygen-sensitive sensor foils. The experiments yielded highly cell line-dependent respiratory activities and oxygen consumption rates. The experiments confirmed a highly expected cell line-specific oxygen uptake and consumption reflecting that different tissue types in the body are also exposed to different oxygen tensions. Experiments carried out with pre-cultured spheroids showed differences in the emerging oxygen gradients beneath the tissue depending on: (i) previous adhesion and cultivation times, (ii) structural properties of the spheroid meaning whether it was densely packed of exhibited a softer, formable structure and (iii) the individual cell line. Vertical oxygen gradients were detected by using triangular glass prisms, with one leg of the prism being covered with the oxygen-sensitive sensor foil. The prisms were suspended in the supernatant medium above adherent cell monolayers. The device allowed for the mapping of vertical oxygen gradients which revealed emerging oxygen concentration gradients depending on the number of metabolically active cells on the surface, the height of the culture medium and the geometry of the respective cell culture vessel. Besides the detection of oxygen concentrations beneath cells as an indicator of their respiration, the pH as the second key parameter was systematically varied in the supernatant medium and several cellular phenotypes were analyzed as a function of pH. Overall, a stronger inhibition of phenotypic behavior was observed for all the cell lines under extracellular acidification than alkaline milieus could increase the phenotypic activity. On the contrary, alkaline conditions even led to a slightly lower cellular response in the case of the cancerous cells.To complete the picture, the intracellular pHi was detected as a function of well-defined extracellular pHe conditions. Intracellular pHi, analyzed with the help of the dye BCECF. The more alkaline the extracellular environment was, the more aligned were the pHi and the pHe value. The studies of this thesis highlight how important a detailed cell characterization is to understand cellular responses to certain stimulations in order to be able to revert to this knowledge in the development of targeted drug design for therapeutics and diagnostics. The last two chapters describe how the experimental techniques to monitor oxygen consumption and phenotypic behavior have been applied in toxicity studies. The influence of BPA on the respiration activity of NRK cells yielded EC50 values between (149 ± 64) µM ((76 ± 5) µM for the time intervall between 6.5 – 9 h of BPA exposure) and (159 ± 235) µM for the sensor spot (SDR®) and sensor foil (VisiSens TD) based experiments, respectively. The influence of glyphosate on the cellular respiration of NRK cells was monitored using the oxygen-sensitive sensor foil. The experiments showed a concentration-independent, slightly inhibited respiration under the exposure to pure glyphosate and a strictly concentration-dependent signal under the influence of glyphosate in the Roundup® formulation with a significantly slower respiration at high concentrations. Complementarily performed studies monitoring the acute toxicity on NRK cells yielded EC50 values between (13.8 ± 0.6) mM (glyphosate) and (4.0 ± 0.7) mM (Roundup®) detected via ECISTM and EC50 values between (19 ± 8) mM (glyphosate) and (3.0 ± 0.2) mM (Roundup®) performed via a PrestoBlueTM cell viability assay