Abstract: Electrical energy demand in the World and particularly in India, is increasing drastically more than its production over a period of time. In order to reduce the demand-supply gap, conserving energy becomes mandatory. Induction motors are the main driving force in the industries and contributes to about half of the total plant energy consumption. By effective monitoring and control of induction motors, huge electricity can be saved. This paper deals about the design and development of such a system, which employs iLON Smart Server and motor performance monitoring nodes. These nodes will monitor the performance of induction motors on-line, on-site and in-situ in the industries. The node monitors the performance of motors by simply measuring the electrical power input and motor shaft speed; coupled to genetic algorithm to estimate motor efficiency. The nodes are connected to the iLON Server through RS485 network. The web server collects the motor performance data from nodes, displays online, logs periodically, analyzes, alerts, and generates reports. The system could be effectively used to operate the motor around its Best Operating Point (BOP) as well as to perform the Life Cycle Assessment of Induction motors used in the industries in continuous operation.
Abstract: Nowadays, illegal logging has been causing many
effects including flash flood, avalanche, global warming, and etc. The
purpose of this study was to maintain the earth ecosystem by keeping
and regulate Malaysia’s treasurable rainforest by utilizing a new
technology that will assist in real-time alert and give faster response
to the authority to act on these illegal activities. The methodology of
this research consisted of design stages that have been conducted as
well as the system model and system architecture of the prototype in
addition to the proposed hardware and software that have been
mainly used such as microcontroller, sensor with the implementation
of GSM, and GPS integrated system. This prototype was deployed at
Royal Belum forest in December 2014 for phase 1 and April 2015 for
phase 2 at 21 pinpoint locations. The findings of this research were
the capture of data in real-time such as temperature, humidity,
gaseous, fire, and rain detection which indicate the current natural
state and habitat in the forest. Besides, this device location can be
detected via GPS of its current location and then transmitted by SMS
via GSM system. All of its readings were sent in real-time for further
analysis. The data that were compared to meteorological department
showed that the precision of this device was about 95% and these
findings proved that the system is acceptable and suitable to be used
in the field.