Prince Mohammad Bin Fahd University

Ahmed Abul Hussain

Ahmed Abul Hasanaath

Samir El-Nakla

Lamya Saad Alqahtani

Munirah Mohammed Aldossary

Hiren Mewada

Fadia Ezzat Elhamami

Rand Alanazi

Nojod Alahmadi

Saja Alherz

Alya Alajmi

Saifullah Shafiq

Lujain Shaker Alawami

Hamad Al-Dossary

Hussain Al-Silham

Lama Khalid Alrimali

Naif M Jan

Mustafa Al-Salem

Reem Raed Alkhater

Haneen Quraishi

Razan Alzaben

Shuruq Fallatah

Tyma Amin Alnasser

Sadiq Ali Alhuwaidi

A T-shaped parking device module having a two-tiered rectangular base, a first support having a cuboid perpendicular to the base, and a second support having a cuboid perpendicular to the first support forming a T-shape. The first support has width X, with both supports having thickness of 0.1×X to 0.25×X. The front side of the second support contains a camera and sound device at center position, LiDAR sensors at first and second ends, a lamp on the first end, and battery and wireless communication node on the second end. A liquid crystal display in a right trapezoidal prism casing is positioned on top of the first end. The device enables simultaneous monitoring of multiple parking spaces through coordinated sensor arrays and wireless communication for comprehensive parking management.

Parking device

A waste management system includes a waste management device, a monitoring unit, and a communication unit. The waste management device includes a collection unit, a classification unit, a segregation unit, a plurality of sensors, a power unit, and a plurality of waste bins. The collection unit collects one or more waste articles. The classification unit utilizes a machine-learning model and identifies a waste category of the one or more waste articles. The segregation unit transports the one or more waste articles to a particular waste bin corresponding to the identified waste category. The power unit supplies power to the waste management device. The monitoring unit monitors the waste management device and controls a resultant action. The communication unit communicates one or more data between a control station and the waste management device using a plurality of IoT devices.

Recycling and disposal unit

Waste collection and sorting apparatus

Waste management system

An insect detection system includes a plurality of traps comprising an attraction source, a communication module, a motion sensor, and one or more environmental sensors. The insect detection system includes a plurality of accelerometers configured to measure vibrations in a tree and is electronically coupled with at least one of the plurality of traps, and one or more power controllers, where each of the power controllers supplies electrical energy to one or more traps and one or more accelerometers. The insect detection system includes a server computer having a processor and a computer readable medium, wherein the server computer is in communication with each trap of the plurality of traps and is configured to receive environmental data from each of the plurality of traps and vibration data from each of the plurality of accelerometers.

Systems and methods for insect detection

A smart driver safety system for a vehicle is described. The system includes a drowsy driver detector, an attention diversion monitor, an automatic mirror adjustment subsystem, and a plurality of actuators. The drowsy driver detector determines a head position of the driver and detects an eye position of the driver's eyes. When the driver's eyes are closed, the drowsy driver detector determines a time duration of an eye closure and compares the time duration to a drowsiness threshold. When the eye closure exceeds the drowsiness threshold, the drowsy driver detector generates a drowsiness alert signal. The attention diversion monitor detects an attention diversion based on the eye position and the eye closure and generates an attention diversion alert signal. The automatic mirror adjustment subsystem adjusts a side mirror of the vehicle based on the eye position and the head position.

Automatic car side-view and rear-view mirrors adjustment and drowsy driver detection system

A system, method, and non-transitory computer readable medium for using a smart collar to monitor a pet are described. The system includes a smart collar, a mobile computing device including a display screen, and a pet monitoring mobile application stored on the mobile computing device. The smart collar includes a global positioning receiver, a communications device, an organic light-emitting diode (OLED) display, a rechargeable battery, and a microcontroller. The microcontroller calculates a distance of a current location of the smart collar from a desired location, determines when the distance is greater than a first distance threshold, and generates a communications packet including the current location, the perimeter, and the distance of the smart collar from the desired location, and transmits the communications packet. The mobile computing device receives the communications packet, and the pet monitoring mobile application displays the current location on a display screen of the mobile computing device.

Torso-mounted farm animal monitoring system

Animal security and location detection method

A communications device includes a uniform linear array of M antennas and a field programmable gate array (FPGA) having pipelined stages in which execution of overlapping instructions estimate a direction of arrival of RF signals from multiple sources. A preprocessing stage of the FPGA includes at least one configurable logic block configured to apply forward/backward averaging spatial smoothing to a signal space matrix extracted from a covariance matrix in the preprocessing stage. The FPGA further includes at least one configurable logic block configured to compute the direction of arrival angle for the RF signals using a least squares method.

Communication system with FPGA DOA arrival estimation

Pipelined field programmable gate array for DOA estimation

Smart collar to track lost pets

FPGA hardware implementation of a novel and computationally efficient DOA estimation method for coherent signals

Growing community of inventors

Dhahran, Saudi Arabia

Ahmed Abul Hussain