ClimateRobo: an autonomous intelligent mobile robot for climate purposes


ClimateRobo is an autonomous intelligent mobile robot for climate purposes, which notifies the weather condition based on environmental data. An ATmega32 microcontroller is used to measure temperature, gas, light intensity, and distance to obstacles using the LM35DZ, MQ-2, photocell, and infrared (IR) sensors. A utility function is proposed to calculate the weather condition according to the temperature and gas data. Afterwards, the weather condition will be monitored on a liquid crystal display (LCD), an appropriate light-emitting diode (LED) will be illuminated, and an audio alarm would be enabled when weather condition is emergency as well as ambient brightness is high. The ambient brightness is calculated by a proposed supervised machine learning using sensed data of the photocell sensor. A fuzzy decision system is proposed to adjust the speed of DC motors based on weather condition and light intensity. The robot can detect and pass stationary obstacles with the six reflective sensors installed in the left, front, and right sides under six detection scenarios. The robot, initially, is simulated in the Proteus simulator and, then, is implemented by electronic circuits and mechanical devices. It would be used by bureau organizations, rescue teams, etc.


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AutoFanSys: an automatic knowledge-based fan system




The fan system uses Analytic Hierarchy Process (AHP) and fuzzy theory to control the speed of fan systems properly. It uses sensing data of three important sensors via the intelligent decision-making procedures. An ATmega16A microcontroller adjusts the speed of a DC motor based on the calculated speed via pulse-width modulation (PWM). Furthermore, speed percentage will be shown on a LCD. Simulation results show that the proposed system reduces total current consumption and total energy consumption compared to another fan system. Firstly, AutoFanSys is designed in Proteus simulator and program file of the microcontroller is generated in CodeVison AVR. Secondly, it is implemented by electromechanical devices to would be applied in real applications (e.g., living room, plant factory, and computer case).



 Here are some of my other planned research projects:

  1. Determining the forward paths of the armed forces toward enemies using fuzzy decision making (it includes three phases: computer simulation, mobile application, and hardware implementation)
  2. A multi-purposes medical automation (with Desktop and Web applications)
  3. A multi-purposes school automation (with Desktop and Web applications)
  4. A smart and intelligent system for traffic control in roads and highways based on Intelligent Transportation System (ITS) (an implementation project)


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