AIMC Topic: Cell Phone

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Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data.

PloS one
Population prediction could provide effective data support for social and economic planning and decision-making, especially for the sub-national population forecasting accurately. In addition to realizing efficient smart population management, this r...

Artificial intelligence-based Raynaud's quantification index (ARTIX): an objective mobile-based tool for patient-centered assessment of Raynaud's phenomenon.

Arthritis research & therapy
BACKGROUND: We aimed to develop an artificial intelligence algorithm able to assess Raynaud's phenomenon (RP) from mobile phone photography, ensuring as a patient-centered, image-based method for RP quantification.

Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone-Based Reading System.

Annals of laboratory medicine
BACKGROUND: Urinalysis, an essential diagnostic tool, faces challenges in terms of standardization and accuracy. The use of artificial intelligence (AI) with mobile technology can potentially solve these challenges. Therefore, we investigated the eff...

Measuring Vertical Jump Height With Artificial Intelligence Through a Cell Phone: A Validity and Reliability Report.

Journal of strength and conditioning research
Erik, HT, Onn, SW, and Montalvo, S. Vertical jump height with artificial intelligence through a cell phone: a validity and reliability report. J Strength Cond Res 38(9): e529-e533, 2024-This study estimated the reliability and validity of an artifici...

Man versus machine: cost and carbon emission savings of 4G-connected Artificial Intelligence technology for classifying species in camera trap images.

Scientific reports
Timely and accurate detection and identification of species are crucial for monitoring wildlife for conservation and management. Technological advances, including connectivity of camera traps to mobile phone networks and artificial intelligence (AI) ...

Real-Time Tracking Data and Machine Learning Approaches for Mapping Pedestrian Walking Behavior: A Case Study at the University of Moratuwa.

Sensors (Basel, Switzerland)
The growing urban population and traffic congestion underline the importance of building pedestrian-friendly environments to encourage walking as a preferred mode of transportation. However, a major challenge remains, which is the absence of such ped...

Development of a Non-Contact Sensor System for Converting 2D Images into 3D Body Data: A Deep Learning Approach to Monitor Obesity and Body Shape in Individuals in Their 20s and 30s.

Sensors (Basel, Switzerland)
This study demonstrates how to generate a three-dimensional (3D) body model through a small number of images and derive body values similar to the actual values using generated 3D body data. In this study, a 3D body model that can be used for body ty...

Fungal bioleaching of metals from WPCBs of mobile phones employing mixed Aspergillus spp.: Optimization and predictive modelling by RSM and AI models.

Journal of environmental management
In the present study, optimization and prediction models for fungal bioleaching for effective metal extraction from waste printed circuit boards (WPCBs) of mobile phones were developed employing central composite design (CCD) of response surface meth...

Light Weight Deep Learning Algorithm for Voice Call Quality of Services (Qos) in Cellular Communication.

Computational intelligence and neuroscience
In this paper, a deep learning algorithm was proposed to ensure the voice call quality of the cellular communication networks. This proposed model was consecutively monitoring the voice data packets and ensuring the proper message between the transmi...

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Scientific reports
Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This study was conducted to validate the accuracy of Convolutional-Neural-Network (CNN) enabled m(mobile...