The disadvantages of the sensor will be avoided with a better insulated design in future work. The result from the study should be useful for future research in designing an oil palm ripeness sensor based on the inductive concept.2.?Basic Principles2.1. StructureThe oil palm ripeness sensor is shown in Figure 1. The oil palm fruit sensor has a rectangular shape. The main parameters of the air coil are its height (outer height, hout and inner height, hin) and width (outer width, wout and inner width, win), which remain constant throughout the experiment. As for length, the outer length, lout and the inner length, l are varied by 1 mm for each type of sensor. Therefore, there are four types of sensor with different lengths being used in the experiment.

All four sensors are designated by their inner air coil lengths, l which are 2, 3, 4 and 5 mm, being tested to observe the effects of the air coil length besides the effects of the coil diameter. To hold the sensor tight and without displacement, the sensor is placed in a holder. Figure 2 shows the holder, where the space with dotted lines is the place where the sensor is to be placed. The fabrication of the sensor uses the plastic Perspect, a non-conducting material that minimizes the flux disturbance in the sensor.Figure 1.Air coil flat-type shape structure (a) top view (b) 3D view.Figure 2.Oil palm ripeness sensor holder.Assuming these four sensors represent a set of sensor, a total of five sets sensors are built
The high volatility of oil prices, coupled with increasing worldwide concerns over CO2 emissions, has led to the evolution of renewable energy concepts over the past few years.

Among others the use of solar photovoltaic (PV), has emerged as the most appropriate solution and has continuously been gaining considerable attention among industry players all around the globe. With the growing demand for clean energy sources, the manufacture and deployment of solar PV cells and photovoltaic arrays have expanded dramatically in the recent years.Monitoring of photovoltaic plants and optimization of the energy they produce is a key issue in order to guarantee this type of plants can serve to their goal of significantly contributing to supply the ever increasing demand of electrical power. Monitoring systems currently available on the Cilengitide market are limited to the evaluation of the average power produced in a given time interval, as a function of several parameters coming from the inverter [1�C6].

Even though relevant, knowing the average power is not enough to either globally evaluate the overall performance of the PV plant or to identify potential failures affecting some plant components (such as single cells or clusters of cells). Instead, it would be very interesting to have information related to how much energy each of the PV panels in the plant is producing.