An Intelligent Big Data Management System Using Haar Algorithm-Based Nao Agent Multisensory Communication

Artificial intelligence (AI) is progressively changing techniques of teaching and learning. In the past, objective was to provide an intelligent tutoring system without intervention from a human teacher enhance skills, control, knowledge construction, intellectual engagement. This paper proposes definition AI focusing on enhancing humanoid agent Nao’s learning capabilities interactions. The aim increase Nao using big data by activating multisensory perceptions such as visual auditory stimuli modules speech-related stimuli, well being in various movements. method develop toolkit enabling Arabic speech recognition implementing Haar algorithm for robust image improve during interactions with child mixed reality data. experiment design testing processes were conducted principle design, namely, three-constituent principle. Four experiments boost level 100 children, different environments (class, lab, home, Leap Motion Controller (LMC). An function operational time cost are developed experience accomplishing best results 4.2 seconds each number recognition. experiments’ showed 3 7 years old compared child’s simple mathematics communication kappa ratio value 90.8%, having corpus that exceeded 390,000 segments, scoring 93% success rate when both vision Nao. uses achieve 94% at distance 0.09 m; LMC reality, hand sign gestures recorded highest accuracy 98.50% algorithm. work shows current enabled gradually higher environment changes perception increases. also cutting-edge research direction fostering child-robots education real time.