Recent developments in the field of microwave planar sensors have led to a renewed interest in industrial, chemical, biological and medical applications that are capable of performing real-time and non-invasive measurement of material properties. Among the plausible advantages of microwave planar sensors is that they have a compact size, a low cost and the ease of fabrication and integration compared to prevailing sensors. However, some of their main drawbacks can be considered that restrict their usage and limit the range of applications such as their sensitivity and selectivity. The development of high-sensitivity microwave planar sensors is required for highly accurate complex permittivity measurements to monitor the small variations among different material samples. Therefore, the purpose of this paper is to review recent research on the development of microwave planar sensors and further challenges of their sensitivity and selectivity. Furthermore, the techniques of the complex permittivity extraction (real and imaginary parts) are discussed based on the different approaches of mathematical models. The outcomes of this review may facilitate improvements of and an alternative solution for the enhancement of microwave planar sensors’ normalized sensitivity for material characterization, especially in biochemical and beverage industry applications.

In this paper, we present a simple design of a T-ring resonator sensor for characterizing solid detection. The sensor is based on a planar microwave ring resonator and operating at 4.2 GHz frequency with a high-quality factor and sensitivity. An optimization of the T-ring geometry and materials were made to achieve high sensitivity for microwave material characterizations. This technique can determine the properties of solid materials from range of 2 GHz to 12 GHz frequencies. Techniques of current microwave resonator are usually measuring the properties of material at frequencies with a wide range; however, their accuracy is limited. Contrary to techniques that have a narrowband which is normally measuring the properties of materials to a high-accuracy with limitation to only a single frequency. This sensor has a capability of measuring the properties of materials at frequencies of wide range to a high-accuracy. A good agreement is achieved between the simulated results of the tested materials and the values of the manufacturer's Data sheets. An empirical equation has been developed accordingly for the simulated results of the tested materials. Various standard materials have been tested for validation and verification of the sensor sensitivity. The proposed concept enables the detection and characterization of materials and it has miniaturized the size with low cost, reusable, reliable, and ease of design fabrication with using a small size of tested sample. It is inspiring a broader of interest in developing microwave planar sensors and improving their applications in food industry, quality control and biomedical materials.

This study presents an application of using Deep Neural Network (DNN) based detector to detect chili and its flower in the chili plant image. Detecting chili on its plant is important for the development of a robotic vision to automatically picking the chili. Only one type of local chili variety is used in this study from the species of Capsicum frustecens. Five hundred of chili plant images were captured from multiple angles and each of images was marked and labelled for any present of chili and its flower. These images were divided into 70-30 per cent proportion for training with validation and testing purposes accordingly. This project uses Faster Regions with Convolutional Neural Networks (R-CNN) as a deep learning model for training that contains around 177 numbers of layers including input and output layers. The classifier network was trained to optimize all parameters involved in chili and its flower classification and detection. The classification and detection accuracy are measured on the tested images. The result shows very good accuracy in validation and testing for classification and detection especially with the image of chili plan is upright position.

An enhanced sensor based on symmetrical split ring resonator (SSRR) functioning at microwave frequencies has been proposed in order to detect and characterize the metal crack of the materials. This sensor is based on perturbation theory, in which the dielectric properties of the material affect the quality factor and resonance frequency of the microwave resonator. Conventionally, coaxial cavity, waveguide, dielectric resonator techniques have been used for characterizing materials. However, these techniques are often large, and expensive to build, which restricts their use in many important applications. Thus, the enhanced bio-sensing technique presents advantages such as high measurement sensitivity with the capability of suppressing undesired harmonic spurious and permits potentially metal crack material detection. Hence, using a High Frequency Structure Simulator (HFSS) software, the enhanced sensor is modeled and the reflection S11 is performed for testing the aluminum metal with crack and without crack at the frequency range of 100 MHz to 3GHz. Variation of crack width and depth has been investigated and the most obvious finding emerged from this study is that the ability of detecting a minimum of sub-millimeter crack width and depth which is a round 10 𝛍m width or depth where the minimum shift of reflected frequency is recorded at 6.2 MHz and 3 MHz for crack width and depth respectively. The enhanced SSRR provides high capability of detecting small crack defection by utilizing the interaction between coupled gap resonators and it is useful for various applications such as aircraft fuselages, nuclear power plant steam generator tubing, and steel bridges and for others that can be compromised by metal fatigue.

The topic of microwave sensors in enclosures is one of the most active areas in material characterization research today due to its wide applications in various industries. Surprisingly, a microwave sensor technology has been comprehensively investigated and there is an industry demand for an accurate instrument of material characterization such as food industry, quality control, chemical composition analysis and bio-sensing. These accurate instruments have the ability to understand the properties of materials composition based on chemical, physical, magnetic, and electric characteristics. Therefore, a design of the T-resonator has been introduced and investigated for an accurate measurement of material properties characterizations. This sensor is designed and fabricated on a 0.787 mm-thickness Roger 5880 substrate for the first resonant frequency to resonate at 2.4 GHz under unloaded conditions. Various standard dielectric of the sample under test (SUT) are tested to validate the sensitivity which making it a promising low-cost, compact in size, ease of fabrication and small SUT preparation for applications requiring novel sensing techniques in quality and control industries.