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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

Towards cognitive artificial intelligence device: an intelligent processor based on human thinking emulation Catherine Olivia Sereati; Arwin Datumaya Wahyudi Sumari; Trio Adiono; Adang Suwandi Ahmad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.14835

Abstract

The intervention of computer technology began the era of a more intelligent and independent instrumentation system based on intelligent methods such as artificial neural networks, fuzzy logic, and genetic algorithm. On the other hand, processor with artificial cognitive ability has also been discovered in 2016. The architecture of the processor was designed based on knowledge growing system (KGS) algorithm, a new concept in artificial intelligence (AI) which is focused on the emulation of the process of the growing of knowledge in human brain after getting new information from human sensory organs. KGS is considered as the main method of a new perspective in AI called as cognitive artificial intelligence (CAI). The design is to obtain the architecture of the data path of the processor. We found that the complexity of the processor circuit is determined by the number of combinations of sensors and hypotheses as the main inputs to the processor. This paper addresses the development of an intelligence processor based on cognitive AI in order to realize an Intelligence Instrumentation System. The processor is implemented in field programmable gate array (FPGA) and able to perform human thinking emulation by using KGS algorithm.
Architecture design for a multi-sensor information fusion processor Catherine Olivia Sereati; Arwin Datumaya Wahyudi Sumari; Trio Adiono; Adang Suwandi Ahmad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.10180

Abstract

This paper discusses the design of the architecture of an information fusion processor. This processor emulates the way of human thinking, namely by drawing conclusions from the obtained collection of information. Architecture design for this processor is based on Knowledge Growing System (KGS) algorithm. KGS is a novelty in Artificial Intelligence field. Compared to other AI methods, KGS focuses on the observation of the process of the knowledge growth within human brain based on information received from the surrounding environment. By using KGS algorithm, this processor works by receiving inputs from a set of sensors and possible hypotheses obtained after the processing of the information. The processor generates a value which is called as Degree of Certainty (DoC), which show the most possible hypothesis among all alternative ones. The Processor Elements which are used to perform KGS algorithm is designed based on systolic array architecture. The design of this processor is realized with VHSIC Hardware Design Language (VHDL) and synthesized by using FPGA Quartus II.13.1. The results show that the data path which has been design is able to perform the mechanism of KGS computation.
P-D controller computer vision and robotics integration based for student’s programming comprehension improvement Nova Eka Budiyanta; Catherine Olivia Sereati; Lukas Lukas
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14881

Abstract

The 21st-century skills needed to face the speed of understanding technology. Such as critical thinking in computer vision and robotics literacy, any student is hampered by the programming that is considered complicated. This study aims at the improvement of student embedded system programming competency with computer vision and mobile robotics integration approach. This method is proposed to attract the students to learn about embedded system programming by delivering integration between computer vision and robotics using the P-D controller since both of the fields are closely related. In this paper, the researcher described computer vision programming to get the data of captured images through the camera stream and then delivered the data into an embedded system to make the decision of robot movement. The output of this study is the improvement of a student’s ability to make an application to integrate a sensor system using a camera and the mobile robot running follow the line. The result of the test shows that the integration method between computer vision and robotics can improve the student’s programming comprehension by 40%. Based on the Feasibility test survey, it can be interpreted that from the whole assessment after being converted to qualitative data, all aspects of the learning stages of programming application tested with the integration of computer vision and robotics fall into the very feasible category for used with a percentage of feasibility by 77.44%.