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“Kamera” Cerdas Untuk Keamanan Rumah & Kota

Kini satu cepis tunggal teknologi network of artificial neural networks (ANNs) siap mendukung keamanan dan kenyamanan kota-kota cerdas (smart-cities), rumah cerdas (smart-homes), interaksi antar-muka manusia-cepis teknologi, pemantauan kondisi kesehatan, dan screening keamanan. Begitu hasil penelitian dan uji-coba teknologi peninderaan ‘kamera’ cerdas Intelligent Electromagnetic (EM) dari Lianlin Li dan koleganya asal Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences di Tiongkok. Hasil riset itu tim ahli itu dirilis oleh jurnal Light Science & Application (volume 8, Article number: 97) edisi November 2019.

Lianlin Li dkk (2019) menciptakan 3 (tiga) ANNs terpadu dan hirarkis guna mengubah-bentuk data gelombang mikro yang terukur menjadi imej-imej seluruh tubuh manusia; cepis tunggal ANN itu mampu memilah titik-titik tubuh seseorang seperti tangan dan dada ke dalam seluruh imej atau gambar; cepis tunggal itu juga mampu mengenali tanda-tangan seseorang secara instan melalui frekwensi Wi-Fi. 2,4 GHz.

Tim ilmuwan itu merincip prinsip kerja ‘kamera cerdas’ EM-nya : “We design a large-aperture programmable coding metasurface for three purposes in one: (1) to perform in-situ high-resolution imaging of multiple people in a full-view scene; (2) to rapidly focus EM fields (including ambient stray Wi-Fi signals) to selected local spots and avoid undesired interferences from the body trunk and ambient environment; and (3) to monitor the local body signs and vital signs of multiple non-cooperative people in real-world settings by instantly scanning the local body parts of interest. Since the switching rate of metasurface is remarkably faster than that of body changing (vital sign and hand sign) by a factor of ~ , the number of people monitored in principle can be very large.”  (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, 6/11/2019).

Uji-coba teknologi cepis tunggal ANN hasil karya cipta Lianlin Li dkk (2019) mampu mencitrakan imej adegan penuh dan pengenalan (recognition) tanda-tangan dan tanda vital lainnya seseorang. Sistem meta-muka (mesurface) cerdas itu juga mampu bekerja dengan secara real-time (tepat-waktu), hemat-energi, dan simultan imager dan recognizer bahkan ketika sinyal-sinyal Wi-Fi semakin mengisi ruang-ruang kehidupan publik sehari-hari akhir-akhir ini. Cepis cerdas imager dan recognizer itu diperkuat oleh satu jaringan ANNS guna mengendalikan aliran data. (Lianlin Li, et al., 2019). 

Hasil riset dan uji-coba teknologi imager dan recognizer dari Lianlin Li dkk (2019) menandai fase baru kemajuan teknologi kota-kota cerdas dan interaksi manusia dan teknologi (Internet of Things / IoT) tanpa memicu risiko-risiko visual privasi seseorang di ruang publik. “Kamera” canggih EM hasil karya Lianlin Li dkk (2019) memudahkan kita ‘melihat’ dari jarak-jauh seseorang, ‘memantau’ perubahan fisiologisnya, dan ‘mendengar’ isi percakapannya.

Menurut Lianlin Li dkk (2019), hasil karya kamera cerdas EM itu tidak melanggar privasi seseorang di ruang publik. “The presented technique can be used to monitor the notable or non-notable movements of non-cooperative people in the real world but also help people with profound disabilities remotely send commands to devices using body languages. This breakthrough could open a new venue for future smart cities, smart homes, human-device interactive interface, healthy monitoring, and safety screening without causing privacy issues.” (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, 6/11/2019). 

Proyek riset itu didanai oleh National Key Research and Development Program of China, National Natural Science Foundation of China, 111 Project. Tim ahli yang terlibat dalam proyek riset itu ialah (1) Lianlin Li asal State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, Beijing, 100871, Tiongkok;

(2) Ya Shuang asal State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, Beijing, 100871, Tiongkok;

(3) Qian Ma  asal State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, 210096, Tiongkok; (4) Haoyang Li asal State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, Beijing, 100871, Tiongkok;

(5) Hanting Zhao asal State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, Beijing, 100871, Tiongkok;

(6) Menglin Wei asal State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, Beijing, 100871, Tiongkok; (7) Che Liu asal State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, 210096, Tiongkok;

(8) Chenglong Hao asal Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117583, Singapura;

(9) Cheng-Wei Qiu, PhD, asal Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117583, Singapura; dan (10) Tie Jun Cui  asal State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, 210096, Tiongkok. Kontribusi Lianlin Li dan Ya Shuang setara dalam karya ilmiah itu.

 

Oleh: Servas Pandur