The purpose of this study is to demonstrate the energy harvesting of power-line magnetic noise. To the best of the authors' knowledge, no research has yet been carried out to confirm this possibility. In this paper, we present a simple circuit design model, and confirm its validity by experimental results. For small self-sufficient devices in a wireless sensor network, the target energy level is 1 mW. We prepare an energy harvesting module with an air-core coil and resonant capacitor. From experimental and simulated results, we investigate the desired conditions for harvesting 1 mW from a uniform magnetic field of 60 Hz. Through experimental results with iron cores, the benefits and drawbacks of the use of a magnetic core are also discussed. With our best harvested module, we successfully demonstrated the energy harvesting of 6.32 mW from a magnetic field of 21.2 μT at 60 Hz. If the usable magnetic flux density increases tenfold, the harvesting energy increased 100-fold. If the magnetic flux density is at an acceptable level in a public space of 200 μT at 60 Hz, the harvesting power density becomes 130 μW/cm ³ . This value is comparable to the value of an energy harvesting module of a light source during a cloudy day.

From the Malaysian harvester’s perspective, the determination of the ripeness of the oil palm (FFB) is a critical factor to maximize palm oil production. A preliminary study of a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunches is presented. To optimize the functionality of the sensor, the frequency characteristics of air coils of various diameters are investigated to determine their inductance and resonant characteristics. Sixteen samples from two categories, namely ripe oil palm fruitlets and unripe oil palm fruitlets, are tested from 100 Hz up to 100 MHz frequency. The results showed the inductance and resonant characteristics of the air coil sensors display significant changes among the samples of each category. The investigations on the frequency characteristics of the sensor air coils are studied to observe the effect of variations in the coil diameter. The effect of coil diameter yields a significant 0.02643 MHz difference between unripe samples to air and 0.01084 MHz for ripe samples to air. The designed sensor exhibits significant potential in determining the maturity of oil palm fruits.

The paper aims to study the sensor that identifies the maturity of oil palm fruit bunches by using a flat-type inductive concept based on a resonant frequency technique. Conventionally, a human grader is used to inspect the ripeness of the oil palm fresh fruit bunch (FFB) which can be inconsistent and inaccurate. There are various new methods that are proposed with the intention to grade the ripeness of the oil palm FFB, but none has taken the inductive concept. In this study, the resonance frequency of the air coil is investigated. Samples of oil palm FFB are tested with frequencies ranging from 20 Hz to 10 MHz and the results obtained show a linear relationship between the graph of the resonance frequency (MHz) against time (Weeks). It is observed that the resonance frequencies obtained for Week 10 (pre-mature) and Week 18 (mature) are around 8.5 MHz and 9.8 MHz, respectively. These results are compared with the percentage of the moisture content. Hence, the inductive method of the oil palm fruit maturity sensor can be used to detect the change in water content for ripeness detection of the oil palm FFB.

The objective of this paper is to provide suitable approximations of effective permeability for magnetic concentration cores. This core has a dumbbell shape so that the magnetic flux is concentrated to the coil winding part of the core. It is well known that the demagnetizing factor strongly depends on the core shape, which defines the effective permeability. Although several researchers have already proposed an approximation for a dumbbell-shaped core, they did not take into account the flange part length. In this paper, a novel approximation for a dumbbell-shaped core is proposed. It is based on the demagnetizing factor and correction terms related to the aspect ratio of both the flange and coil winding part. From experimental results, the validity of the approximation is confirmed.

This paper presents a novel approach for the design of square coil system, through considerations of a conventional square coil system. This simple approach allows us to design a coil system which contains a greater number of coils. From this design method, we introduce a new structure system of same-sized square coils, Simple-Box-9. The constant coil spacing is a fourth-part of the side length of the coil, and the number of windings is 2/1/1/1/1/1/1/1/2. From numerical calculations and experiments, it is shown that Simple-Box-9 can achieve the best uniformity compared with conventional square coil systems.

Oil palm ripeness’ main evaluation procedure is traditionally accomplished by human vision. However, the dependency on human evaluators to grade the ripeness of oil palm fresh fruit bunches (FFBs) by traditional means could lead to inaccuracy that can cause a reduction in oil palm fruit oil extraction rate (OER). This paper emphasizes the fruit battery method to distinguish oil palm fruit FFB ripeness stages by determining the value of load resistance voltage and its moisture content resolution. In addition, computer vision using a color feature is tested on the same samples to compare the accuracy score using support vector machine (SVM). The accuracy score results of the fruit battery, computer vision, and a combination of both methods’ accuracy scores are evaluated and compared. When the ripe and unripe samples were tested for load resistance voltage ranging from 10 Ω to 10 kΩ, three resistance values were shortlisted and tested for moisture content resolution evaluation. A 1 kΩ load resistance showed the best moisture content resolution, and the results were used for accuracy score evaluation comparison with computer vision. From the results obtained, the accuracy scores for the combination method are the highest, followed by the fruit battery and computer vision methods.