Humidity measurement is one of the most significant issues in various areas of applications such as instrumentation, automated systems, agriculture, climatology and GIS. Numerous sorts of humidity sensors fabricated and developed for industrial and laboratory applications are reviewed and presented in this article. The survey frequently concentrates on the RH sensors based upon their organic and inorganic functional materials, e.g., porous ceramics (semiconductors), polymers, ceramic/polymer and electrolytes, as well as conduction mechanism and fabrication technologies. A significant aim of this review is to provide a distinct categorization pursuant to state of the art humidity sensor types, principles of work, sensing substances, transduction mechanisms, and production technologies. Furthermore, performance characteristics of the different humidity sensors such as electrical and statistical data will be detailed and gives an added value to the report. By comparison of overall prospects of the sensors it was revealed that there are still drawbacks as to efficiency of sensing elements and conduction values. The flexibility offered by thick film and thin film processes either in the preparation of materials or in the choice of shape and size of the sensor structure provides advantages over other technologies. These ceramic sensors show faster response than other types.
As the main exporter in the oil palm industry, the need to improve the quality of palm oil has become the main interest among all the palm oil millers in Malaysia. To produce good quality palm oil, it is important for the miller to harvest a good oil palm Fresh Fruit Bunch (FFB). Conventionally, the main reference used by Malaysian harvesters is the manual grading standard published by the Malaysian Palm Oil Board (MPOB). A good oil palm FFB consists of all matured fruitlets, aged between 18 to 21 weeks of antheses (WAA). To expedite the harvesting process, it is crucial to implement an automated detection system for determining the maturity of the oil palm FFB. Various automated detection methods have been proposed by researchers in the field to replace the conventional method. In our preliminary study, a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunch was proposed. The design of the proposed air coil sensor based on the inductive sensor was further investigated mainly in the context of the effect of coil diameter to improve its sensitivity. In this paper, the sensitivity of the inductive sensor was further examined with a dual flat-type shape of air coil. The dual air coils were tested on fifteen samples of fruitlet from two categories, namely ripe and unripe. Samples were tested within 20 Hz to 10 MHz while evaluations on both peaks were done separately before the gap between peaks was analyzed. A comparative analysis was conducted to investigate the improvement in sensitivity of the induction-based oil palm fruit sensor as compared to previous works. Results from the comparative study proved that the inductive sensor using a dual flat-type shape air coil has improved by up to 167%. This provides an indication in the improvement in the coil sensitivity of the palm oil fruit sensor based on the induction concept.
This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical Capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline. Previous works only focused on estimating the oil fraction in the pipeline based on fixed ECT sensor parameters. With fixed ECT design sensors, an oil fraction neural sensor can be trained to deal with ECT data based on the particular sensor parameters, hence the neural sensor is not generic. This work focuses on development of a generic neural oil fraction sensor based on training a Multi-Layer Perceptron (MLP) ANN with various ECT sensor parameters. On average, the proposed oil fraction neural sensor has shown to be able to give a mean absolute error of 3.05% for various ECT sensor sizes.
For the past decade, much attention was focused on polysaccharide natural resources for various purposes. Throughout the works, several efforts were reported to prepare new function of chitosan by chemical modifications for renewable energy, such as fuel cell application. This paper focuses on synthesis of the chitosan derivative, namely, O-nitrochitosan which was synthesized at various compositions of sodium hydroxide and reacted with nitric acid fume. Its potential as biopolymer electrolytes was studied. The substitution of nitro group was analyzed by using Attenuated Total Reflectance Fourier Transform Infra-Red (ATR-FTIR) analysis, Nuclear Magnetic Resonance (NMR) and Elemental Analysis (CHNS). The structure was characterized by X-ray Diffraction (XRD) and its thermal properties were examined by using differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA). Whereas, the ionic conductivity of the samples was analyzed by electrochemical impedance spectroscopy (EIS). From the IR spectrum results, the nitro group peaks of O-nitrochitosan, positioned at 1646 and 1355 cm-1, were clearly seen for all pH media. At pH 6, O-nitrochitosan exhibited the highest degree of substitution at 0.74 when analyzed by CHNS analysis and NMR further proved that C-6 of glucosamine ring was shifted to the higher field. However, the thermal stability and glass transition temperatures were decreased with acidic condition. The highest ionic conductivity of O-nitrochitosan was obtained at ~10-6 cm-1. Overall, the electrochemical property of new O-nitrochitosan showed a good improvement as compared to chitosan and other chitosan derivatives. Hence, O-nitrochitosan is a promising biopolymer electrolyte and has the potential to be applied in electrochemical devices.