TY  - JOUR
T1  - An Efficient Architectural Model for Building Cognitive Expert System
Related to Traffic Management in Smart Cities
AU - Kamesh, D.B.K. AU - Sumadhuri, D.S.K. AU - Sahithi, M.S.V. AU - Sastry, J.K.R. 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 9
SP  - 2437
EP  - 2445
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.2437.2445
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.2437.2445
KW  - Smart city
KW  -intelligent systems
KW  -cognitive expert system
KW  -traffic management system
KW  -India
AB  - One of the major goals of developing countries is to build smart cities to avoid different kinds of
congestions, accidents and many kinds of inordinate delays. The most important consideration is intelligent
traffic management system. An intelligent traffic management system can be conceived through many of
individual sub-systems which include Bio-sensing system, imaging system, messaging system, cognitive
system and visualization system, remote sensing and communication system. Each of the sub-system while is
expected to research independently it should also be in existence in unison along with other sub-systems. To
implement automated traffic control system there is a need of cognitive subset which is the decisive-core of the
integrated system. It essentially researches like a virtual human operator. An embedded remote-control takes
in various traffic conditions such as undetected accidents, VIP movement and abnormal environmental
conditions as inputs from the police force to the cognitive control system to control the traffic flows at signal
post systems. Designing a cognitive subsystem with high precision, to take real-time decisions with varying
multiple inputs is a complex task. It should take inputs from all the other subsystems and the man-operator,
process the gathered data and then issue control signals accordingly. This study emphasises on the design
and application of the cognitive expert system in a simple yet efficient manner to suite the smart city
environment.
ER  -