Autonomous wheelchairs are important tools to enhance the mobility of people with disabilities. Advances in computer and wireless communication technologies have contributed to the provision of smart wheelchairs to suit the needs of the disabled person. This research paper presents the design and implementation of a voice controlled electric wheelchair. This design is based on voice recognition algorithms to classify the required commands to drive the wheelchair. An adaptive neuro-fuzzy controller has been used to generate the required real-time control signals for actuating motors of the wheelchair. This controller depends on real data received from obstacle avoidance sensors and a voice recognition classifier. The wheelchair is considered as a node in a wireless sensor network in order to track the position of the wheelchair and for supervisory control. The simulated and running experiments demonstrate that, by combining the concepts of soft-computing and mechatronics, the implemented wheelchair has become more sophisticated and gives people more mobility.

Fish farming is still controlled and managed in the traditional way where water quality and fish feeding are manually controlled. There is a need to use computer and communication technology in fish farms for remote monitoring and control. This paper deals with the design and implementation of an internet of things (IoT) based system for real-time monitoring, control and management of fish farming. The design of such a system is based on measuring different types of variables and using the information to control fish growth and increase productivity. Each fish pond is a node in a wireless sensor network. The node contains an embedded microcontroller connected to a set of sensors and actuators and a wireless communication module. Two fuzzy controllers are designed to control the water quality in the ponds as well as the environment using five sensors in each pond plus three environmental sensors. Practical results indicate the accuracy of the measurement system compared to the results obtained from commercial devices used on the farm. These results also showed that the proposed approach achieves the best performance of the real-time monitoring and control system in fish ponds.

The paper describes a novel method of rotor-position sensing of permanent-magnet machines, which requires no encoder nor any modification to conventional machines. The machine is electronically commutated, by virtue of position sensing, achieved through measuring the modulation in the inverter carrier frequency component, caused by the positional variation in motor winding impedance. A closed-loop speed control system drives the motor with precision and at maximum efficiency for a wide range of load and speed.

A novel form of rotor position sensing is described that makes use of a simple search coil system in a permanent magnetic machine. It can be used for almost any field configuration and permanent magnet material provided that there is a reluctance variation between the direct and quadrature axes. Practical results are presented for a particular rotor configuration. A closed-loop speed control system gives precise speed control and operation at high efficiency. This enables a complete drive system to be implemented, involving torque angle control for optimal performance.

This paper presents design and implementation of a monitoring and fault detection for photovoltaic renewable energy system. A real-time monitoring unit based on wireless sensor networks is designed to monitor required variables related to each module and unit in the PV system. An intelligent algorithm based onfuzzy logic has been developed to detect and locate faults. A mathematical model together with an experimental prototype is designed to evaluate the performance of the proposed PV system under normal and faulty conditions. The obtained results from both simulated and experimental systems confirm that the implemented monitoring and fault detection system perform the required tasks with acceptable accuracy and cost. Applying real-time remote monitoring is easier to specify faults and observe the overall performance of any solar PV system.

Epidemic diseases patients need constant monitoring of their health, whether in the hospital or at home, and this requires great costs. The employment of information and communication technologies and artificial intelligence concepts helps reduce these costs. This paper introduces a real-time monitoring system for monitoring pneumonia patients that will allow doctors to monitor the health of their patients remotely through smartphones or internet-connected devices. To verify the proper functioning of this system, a real-time monitoring device was developed. A secure mechanism is designed to establish a wireless connection to the monitoring unit.