TINJAUAN LITERATUR: POTENSI EEG-BASED BRAIN-COMPUTER INTERFACE UNTUK DESENTRALISASI KONTROL NEURAL PADA EKOSISTEM INTERNET OF AUTONOMOUS THINGS (IOAT)
DOI:
https://doi.org/10.54314/jssr.v8i4.5071Abstract
Abstract: EEG-based Brain Computer Interface offers the potential for integration with Internet of Autonomous group control such as drones, robots, wheelchairs, AUVs, smart-home and smart-city devices, etc. This literature review aims to determine the potential for integration (BCI) in controlling smart devices and swarm intelligence within the IoAT ecosystem that collaborates in a corporate and decentralized manner. As well as compiling an initial abstract framework towards this development direction, based on a review of journals related to brain-computer interfaces, intent translator frameworks for IoT, LLM, mesh topology, federated learning, swarm-rules models, and human-swarm cybernetic/feedback loop integration. The results of the review show that BCI-IoAT integration through a swarm intelligence approach has the potential to create a robust, independent, and autonomous system.
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Keywords: Brain Computer Interface; EEG; Swarm intelligence; IoT; LLM; human-swarm; Autonomous Things
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Abstrak: Brain Computer Interface berbasis EEG menawarkan potensi integrasi dengan kendali kelompok Internet Of Autonomous seperti drone, robot, kursi roda, AUV, perangkat smart-home dan smart-city, dsb. literature review ini bertujuan untuk mengetahui potensi integrasi (BCI) dalam mengendalikan perangkat pintar dan swarm intelligence di dalam ekosistem IoAT yang bekerja sama secara korporatif dan desentraliasi. Serta menyusun kerangka abstrak awal menuju arah pengembangan tersebut, berdasarkan review jurnal-jurnal yang berhubungan dengan brain-computer interface, framework intent translator for IoT, LLM, topologi mesh, federated learning, model swarm-rules, dan integrasi human-swarm cybernetic/feedback loop. Hasilnya tinjauan menunjukkan bahwa integrasi BCI-IoAT melalui pendekatan swarm intelligence berpotensi menciptakan sistem yang bersifat robust, mandiri, dan otonom.
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Kata kunci: Brain Computer Interface; EEG; Swarm intelligence; IoT; LLM; human-swarm; Autonomous Things
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