Please wait a minute...
JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)  2017, Vol. 51 Issue (8): 1662-1668    DOI: 10.3785/j.issn.1008-973X.2017.08.024
Electrical and Electronic Engineering     
Research of sentient city under guidance of new concept
MENG Jun, XU Wen-yuan, ZHAO Xi-meng
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Download:   PDF(1512KB) HTML
Export: BibTeX | EndNote (RIS)      

Abstract  

A new concept was proposed to achieve a goal that machine can proactively sense human information, such as physiological states, emotions and behaviors, and provide effective interventions for human and environment. The core of the concept is that machine senses human information proactively and spontaneously. The new concept was compared with a similar concept, ambient intelligence. The core and components of sentient city was elaborated based on the new concept. A coupling relation between information and devices was proposed. A platform of sentient city was constructed. The platform is centered on the core that machine proactively senses human information and environment can spontaneously adapt to human. The platform was compared with a platform proposed by IBM. An example of a chair was taken to illustrate how to achieve the goal that machine proactively senses human information, self-regulation of environment and make the environment fit human in a Sentient City.



Received: 15 July 2016      Published: 16 August 2017
CLC:  TP18  
Cite this article:

MENG Jun, XU Wen-yuan, ZHAO Xi-meng. Research of sentient city under guidance of new concept. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(8): 1662-1668.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2017.08.024     OR     http://www.zjujournals.com/eng/Y2017/V51/I8/1662


基于新概念的“感知城市”探索

为了实现机器主动感知人体的生理状态、情感和行为等人体状态信息、实现机器对人体的行为和环境的有效干预,提出以机器感知人体为核心的新概念,与现有的环境智能概念进行对比;基于新概念详细分析"感知城市"的核心、关键组成等要素,提出信息与信息采集设备之间所具有的耦合关系;构建以机器主动感知人体、环境自主适应人体为核心的"感知城市"平台,与IBM提出的"感知城市"平台进行对比;以"椅子"为例,具体阐述在"感知城市"中如何实现机器主动感知人体、如何在感知人体状态信息后实现环境的自主调节.与现有的环境智能和感知城市对比,结果表明,所提出的概念和平台,可以实现机器的主动感知和有效干预.

[1] REMAGNINO P, FORESTI G L. Ambient intelligence:A new multidisciplinary paradigm[J]. IEEE Transactions on systems, man, and cybernetics-Part A:Systems and humans, 2005, 35(1):1-6.
[2] CHARALAMPIDOU M, MOUROUTSOS S, PAVLIDIS G. Identifying aspects of Ambient Intelligence through a review of recent developments[J]. Journal of Advanced Computer Science & Technology, 2012, 1(3):82-100.
[3] AARTS E, WICHERT R. Technology Guide[M].. Berlin:Springer, 2009:244-249.
[4] KOVÁCS G L, KOPÁCSI S. Some aspects of ambient intelligence[J]. Acta Polytechnica Hungarica, 2006, 3(1):35-60.
[5] JOSÉ R, RODRIGUES H, OTERO N. Ambient intelligence:beyond the inspiring vision[J]. Journal of Universal Computer Science, 2010, 16(12):1480-1499.
[6] GRAHAM S, MARVIN S. Planning cyber cities:Integrating telecommunications into urban planning[J]. Town Planning Review, 1999, 70(1):89.
[7] ISHIDA TORU, ISBISTER KATHERINE. Digital cities:technologies, experiences, and future perspectives[M]. Berlin:Springer Science & Business Media, 2000:1-57.
[8] KOMNINOS N. Intelligent cities:innovation, knowledge systems, and digital spaces[M]. Abingdon:Taylor & Francis, 2002:118-208.
[9] HOLLANDS R G. Will the real smart city please stand up? Intelligent, progressive or entrepreneurial[J].City, 2008, 12(3):303-320.
[10] SHEPARD M. Sentient city:Ubiquitous computing, architecture, and the future of urban space[M]. Cambridge:The MIT press, 2011:1-200.
[11] GREENFIELD A. Everyware:The dawning age of ubiquitous computing[M]. Berkeley:New Riders, 2010:1-34.
[12] KITCHIN R. The real-time city? Big data and smart urbanism[J]. GeoJournal, 2014, 79(1):1-14.
[13] THRIFT N. The ‘sentient’ city and what it may portend[J]. Big Data & Society, 2014, 1(1):1-21.
[14] MAYER-SCHONBERGER V. Big data:a revolution that will transform how we Live, work, and think[M]. London:John Murray, 2013:181-183.
[15] HILDEBRANDT M, VRIES K D. Privacy, Due process and the computational turn:The philosophy of law meets the philosophy of technology[M]. London:Routledge, 2013:121-42.
[16] SHETH A. Citizen sensing, social signals, and enriching human experience[J]. IEEE Internet Computing, 2009, 13(4):87.
[17] KOCH F, CARDONHA C, GENTIL J M, et al. Citizen in sensor networks[M]. Berlin:Springer, 2013:57-66.
[18] BUCHANAN M. Behavioural science:secret signals[J]. Nature, 2009, 457(7229):528-530.
[19] PENTLAND A. To signal is human[J]. American Scientist, 2010, 98(3):204-211.
[20] STONEHAM A M, GAUGER E M, PORFYRAKIS K, et al. A new type of radical-pair-based model for magnetoreception[J]. Biophysical journal, 2012, 102(5):961-968.
[21] LAMBERT N, CHEN Y N, CHENG Y C, et al. Quantum biology[J]. Nature Physics, 2013, 9(1):10-18.
[22] BALL P. The dawn of quantum:biology[J]. Nature, 2011, 474(7351):272-274.
[23] KARLEN W, MATTIUSSI C, FLOREANO D. Sleep and wake classification with ECG and respiratory effort signals[J]. IEEE Transactions on Biomedical Circuits and Systems, 2009, 3(2):71-78.
[24] DING F, O'DONNE J, XU Q, et al. Changes in the composition of brain interstitial ions control the sleep-wake cycle[J]. Science, 2016, 352(6285):550-555.
[25] HASSELBERG M J, MCMAHON J, PARKER K. The validity, reliability, and utility of the iButton® for measurement of body temperature circadian rhythms in sleep/wake research[J]. Sleep medicine, 2013, 14(1):5-11.

[1] WANG Kai, YUE Bo-xuan, FU Jun-wei, LIANG Jun. Image restoration and fault tolerance of stereo SLAM based on generative adversarial net[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2019, 53(1): 115-125.
[2] MENG Jun, DENG Xiao-yu, YU Jie-zhou. Postoperative survival prediction model of BP neural network with variable cluster[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(12): 2365-2371.
[3] LIU Ru-hui, HUANG Wei-ping, WANG Kai, LIU Chuang, LIANG Jun. Semi-supervised constraint ensemble clustering by fast search and find of density peaks[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(11): 2191-2200.
[4] HU Li-sha, WANG Su-zhen, CHEN Yi-qiang, GAO Chen-long, HU Chun-yu, JIANG Xin-long, CHEN Zhen-yu, GAO Xing-yu. Fall detection algorithms based on wearable device: a review[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(9): 1717-1728.
[5] GUO Bao-zhen, ZUO Wan-li, WANG Ying. Double CNN sentence classification model with attention mechanism of word embeddings[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(9): 1729-1737.
[6] WANG Hong-kai, CHEN Zhong-hua, ZHOU Zong-wei, LI Ying-ci, LU Pei-ou, WANG Wen-zhi, LIU Wan-yu, YU Li-juan. Evaluation of machine learning classifiers for diagnosing mediastinal lymph node metastasis of lung cancer from PET/CT images[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(4): 788-797.
[7] CHEN Xing-yu, HUANG Shan-he, He Hao-zhe. Measurement error due to frequency selection in multi-frequency suspended sediment measurement system[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(2): 307-316.
[8] YU Jian-bo, DONG Chen-yang, LI Chuan-feng, LIU Hai-qiang. Statistical α-algorithm based process mining on clinical pathway[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(10): 1881-1890.
[9] ZHANG Yu-hong, HU Xue-gang, YANG Qiu-jie. A feature selection approach suitable for
data stream classification
[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2011, 45(12): 2247-2251.
[10] CHEN Jing, ZHANG Shu-Wei, BO Wang-Hui. Instance feedback of product design based on tentative design chain[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2010, 44(3): 440-447.
[11] HU Bin, GAO Ji, GUO Hang. Dynamic model of normative multi-agent system and its property verification mechanism[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2009, 43(6): 1014-1019.
[12] LI Wei, BANG Gao-Yu, TAO Li-Sen, et al. Real-coded immune-tabu hybrid algorithm to solve constrained optimization problems[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2009, 43(6): 1037-1041.
[13] CHEN Meng-Liang. Agent-network:a fusion method for heterogeneous business intelligence technologies[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2009, 43(6): 1053-1059.