Prince Mohammad Bin Fahd University

Ahmed Abul Hasanaath

Ahmed Abul Hussain

Hiren Mewada

Munirah Mohammed Aldossary

Fadia Ezzat Elhamami

Lamya Saad Alqahtani

Nazeeruddin Mohammad

Majid Ali Khan

Saifullah Shafiq

Lama Khalid Alrimali

Tyma Amin Alnasser

Lujain Shaker Alawami

Reem Raed Alkhater

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

A system and methods for assessing road surface quality includes a wireless mobile device having a camera, a location receiver, and a road surface classifying computer application and is configured to be mounted on a vehicle. The system has a remote server having a road surface classifying web application, a database, and an interactive map connected to the web application. The mobile device actuates the camera to record videos, extract images from the videos, process the images, classify the images into road conditions, record a location of the images, generate a data packet including an identification of the mobile device and a time stamp of the data packet, and transmit the data packet to the remote server. The remote server stores the data packet in the database. The web application superimposes the time stamp of the data packet, the location, the road conditions, and the images on the interactive map.

Automated road surface condition quality assessment using smart (IoT) devices

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

Growing community of inventors

Dhahran, Saudi Arabia

Ahmed Abul Hasanaath