Slamet Widodo

Moving Object Localization Using Sound-Based Positioning System with Doppler Shift Compensation

Sound-based positioning systems are a potential alternative low-cost navigation system. Recently, we developed such an audible sound-based positioning system, based on a spread spectrum approach. It was shown to accurately localize a stationary object. Here, we extend this localization to a moving object by compensating for the Doppler shift associated with the object movement. Numerical simulations and experiments indicate that by compensating for the Doppler shift, the system can accurately determine the position of an object moving along a non-linear path. When the object moved in a circular path with an angular velocity of 0 to 1.3 rad/s, it could be localized to within 25 mm of the actual position. Experiments also showed the proposed system has a high noise tolerance of up to −25 dB signal-to-noise ratio (SNR) without compromising accuracy.

Sound-Based ranging system in greenhouse environment with multipath effect compensation using artificial neural network

In this study, sound-based ranging system in greenhouse environment with compensation of measurement error caused by multipath effect using Artificial Neural Network (ANN) was proposed. Greenhouse environment has special characteristic which is different with condition where the similar system that previously developed were applied. There are challenges need to be handled in developing accurate ranging system in greenhouse such as high humidity, temperature gradient, wind, and obstacles. In this study, error compensation was performed by first estimating the measurement error using some features extracted from the cross-correlation wave of the received signal by using ANN. Then, the estimated value was used to compensate the measurement error. The experiment result showed the feasibility to apply the proposed method to improve accuracy of sound-based ranging system in greenhouse environment.

Design of Self-calibration Method for Sound-based Positioning System in Greenhouse

Abstract There is a promising potential to use sound-based positioning system as low cost platform for automation and robotic system in agriculture. It can provide high positioning accuracy with relatively low cost. For practical use, it is important to make deployment of this system become simple and easy. Therefore, self-calibration method is highly demanded to replace manual calibration which is laborious, impractical, and time consuming. Here, we proposed a self-calibration method for sound-based positioning system in greenhouse. Experiment and numerical simulation were conducted to evaluate the performance of the proposed method. Experimental result shows that by using the proposed method, calibration of the sound-based positioning system in 7 m x 16 m area can be done with relatively small error, about 2-5 cm. We also investigated the performance of the proposed method under different greenhouse conditions, to see the influence of wind and temperature. Although there are some limitations, this study shows the feasibility to use the proposed system in greenhouse or other places with relatively flat floor.

Machine Vision-Based Analysis for Black Tea Quality Evaluation

Currently, visual quality evaluation of black tea production depends only on expert labor judgement. This allows biases and inconsistency in the end product caused by unstandardized methods. Therefore, it is proposed that machine vision could be applied in order to standardize the quality evaluation method. The goal of this research is to build a machine vision-based system to classify quality classes of black tea. In this research black tea classes used are class I, class II, and class III without considering the grade for each class. A neural network classifier was used to classify black tea images with seven nodes, one hidden layer. Ten features were used as an input for the classifier, RGB, index RGB, R/G, R/B, magenta, and yellow. From the results, the system achieved an accuracy of 100%. Application of machine vision technology in black tea production could not only support sustainability in agriculture, but also can also be used for precision agriculture in practical fields.

Development of a laser-based localization system in an outdoor setting: Design and performance evaluation of transmitter and receiver component

The Global Positioning System (GPS) has been widely used as guidance for autonomous vehicles and robots, especially in outdoor environments. For such application a high accuracy of GPS is required (e.g. using a Real-Time Kinematics Differential GPS). however, it is costly. This paper discuss about development of a laser-based localization system in outdoor setting which works based on triangulation as an alternative of positioning system as a guidance of agricultural machinery operation in a specified field operation such as fertilizer application or chemical sprayer operation. More specific this paper discuss about design and performance analysis of laser transmitter and receiver component of the proposed system. The main challenges in designing those components is that the system should be capable of dealing with influencing factors exist in outdoor environment, especially ambient light. Here, modulation technique applied to the transmitter combined with high pass filter applied to the receiver is used to address that issue. The experiment results showed that using transmitter with laser modulated at 2.7 kHz and receiver with 1.5 kHz cut-off high pass filter worked best on 50% duty cycle. The developed transmitter-receiver system was capable of reaching up to 200 m distance and worked well on a various ambient light conditions. This result suggested that the developed prototype can be used to further develop the proposed laser based localization system.

Sistem Kontrol Tinggi Muka Air Untuk Budidaya Padi

This research aims to design a control system to keep the water level and soil moisture at a level that is suitable to the plant requirment and determines the optimum water level and soil moisture in each growth phase of paddy field cultivation. The water level control system was formed based on on-off controls system using Arduino Uno ATMega328P microcontroller. When the sensor gives input that the water level is below the set points, then microcontroller will command the irrigation valve to open and the drainage valve to close. The volume and time of irrigation and drainage control are dependent to set point. Set point was controlled based on water regime treatment. Water regime consisted of three treatments, which are wet regime (RB), slightly wet regime (RAB), and dry regime (RK). The research result showed that control system was very effective and efficient in controlling the water regime according to the control algorithms. Besides, the research result showed that the water regimes affected the plant growth, land productivity, and water productivity. Treatment of wet regime (RAB) gave the highest number of tiller (138 tillers), yield 194.7 g/hill (equal to 21 ton/ha with assumption of 30 cm x 30 cm spacing) and water productivity 3.16 kg/m3.