scholarly journals A Weight-Aware Recommendation Algorithm for Mobile Multimedia Systems

2013 ◽  
Vol 9 (2) ◽  
pp. 139-155 ◽  
Author(s):  
Pedro M. P. Rosa ◽  
Joel J. P. C. Rodrigues ◽  
Filippo Basso
Keyword(s):  
Data Fusion ◽  
Mobile Application ◽  
Recommendation System ◽  
Multimedia Systems ◽  
Gps Receiver ◽  
Location Data ◽  
Data User ◽  
Current Growth ◽  
Time Awareness ◽  
General User

In the last years, information flood is becoming a common reality, and the general user, hit by thousands of possible interesting information, has great difficulties identifying the best ones, that can guide him in his/her daily choices, like concerts, restaurants, sport gatherings, or culture events. The current growth of mobile smartphones and tablets with embedded GPS receiver, Internet access, camera, and accelerometer offer new opportunities to mobile ubiquitous multimedia applications that helps gathering the best information out of an always growing list of possibly good ones. This paper presents a mobile recommendation system for events, based on few weighted context-awareness data-fusion algorithms to combine several multimedia sources. A demonstrative deployment were utilized relevance like location data, user habits and user sharing statistics, and data-fusion algorithms like the classical CombSUM and CombMNZ, simple, and weighted. Still, the developed methodology is generic, and can be extended to other relevance, both direct (background noise volume) and indirect (local temperature extrapolated by GPS coordinates in a Web service) and other data-fusion techniques. To experiment, demonstrate, and evaluate the performance of different algorithms, the proposed system was created and deployed into a working mobile application providing real time awareness-based information of local events and news.

The Mining of Urban Hotspots Based on Multi-source Location Data Fusion

2021 ◽  
pp. 1-1
Author(s):  
Li Cai ◽  
Haoyu Wang ◽  
Cong Sha ◽  
Fang Jiang ◽  
Yihang Zhang ◽  
...  
Keyword(s):  
Data Fusion ◽  
Source Location ◽  
Location Data

A Low-Cost, High Rate Motion Software Sensor System Based on Novel Data Fusion for Unmanned Surface Vehicle Navigation and Oceanographic Instrumentation Motion Correction

2011 ◽  
Author(s):  
Chrystel R. Gelin ◽  
Nikolaos I. Xiros
Keyword(s):  
Data Fusion ◽  
Low Cost ◽  
Underwater Vehicles ◽  
High Rate ◽  
Measurement Unit ◽  
Vehicle Navigation ◽  
Gps Receiver ◽  
Unmanned Surface Vehicle ◽  
Flux Gate ◽  
Tilt Sensor

One of the major challenges in the navigation of underwater vehicles is obtaining precise and reliable positioning updates. Dead-Reckoning aided with Doppler velocity measurement has been, and remains, the most common method for underwater navigation for small vehicles. DR uses a set of navigation instruments to estimate the position of the vehicle by integrating the body-fixed velocity, accelerations, and angular rates with respect to time. Instrument error and bias lead to position error that increases exponentially with time. Thus, current DR systems require frequent position recalibrations. The Global Positioning System (GPS) provides measurements of geodetic coordinates for air and surface vehicles and it is often used to correct positioning error. However, underwater vehicles cannot use GPS for inflight navigation because GPS signals only penetrate a few centimeters past the air-sea interface. Thus, underwater vehicle navigation systems are limited to periodic position update from the GPS when they surface and extend an antenna through the air-sea interface. Standard GPS receivers are unable to provide the rate or precision required when used on a small vessel such as an Unmanned Surface Vehicle (USV). To overcome this, a low cost high rate motion measurement system for an USV with underwater and oceanographic purposes is proposed. The proposed onboard system for the USV consists of an Inertial Measurement Unit (IMU) with accelerometers and rate gyros, a GPS receiver, a flux-gate compass, a roll and tilt sensor and an ADCP. Interfacing all the sensors proved rather challenging because of their different characteristics. Some of the instruments have digital output (Compass/ADCP/GPS) while others have an analog output (IMU/tilt sensor). The proposed data fusion technique integrates the IMU, GPS receiver, flux-gate compass as well as tilt sensor and develops an embeddable software package, using real time data fusion methods, for a USV to aid in navigation and control as well as controlling an onboard Acoustic Doppler Current Profiler (ADCP). While ADCPs non-intrusively measure water flow, they suffer from the inability to distinguish between motions in the water column and self-motion. Thus, the vessel motion contamination needs to be removed to analyze the data and the system developed in this text provides the motion measurements and processing to accomplish this task.

scholarly journals Quantification of the Accuracy of Low Priced GPS Receivers for Crash Location

2010 ◽  
Author(s):  
Thobias Sando ◽  
Renatus Mussa ◽  
John Sobanjo ◽  
Lisa Spainhour
Keyword(s):  
Global Positioning System ◽  
Time Of Day ◽  
Gps Data ◽  
Positioning System ◽  
Gps Receiver ◽  
Accuracy Improvement ◽  
Gps Receivers ◽  
Location Data ◽  
Global Positioning ◽  
Potential Tool

Global positioning system (GPS) has been identified as a potential tool for capturing crash location data. This study quantifies factors that could affect the accuracy of GPS receivers. The results showed that GPS receiver orientation, site obstructions, and weather have significant effects on the accuracy of GPS receivers. Time of day and number of satellites were not found to significantly affect the accuracy of GPS receivers. HDOP values of 1.2 or less were found to be adequate for crash location purposes. An accuracy improvement of 20.7% was realized by filtering GPS data based on HDOP values.

scholarly journals Low Cost Intelligent Child Safety Wearable IoT Device for India

2020 ◽  
Vol 9 (1) ◽  
pp. 2367-2370
Keyword(s):  
Mobile Application ◽  
High Reliability ◽  
Low Cost ◽  
Gps Receiver ◽  
Common People ◽  
Only Children ◽  
Voice Message ◽  
Smart Wearable ◽  
Present World ◽  
Intelligent Child

in this present world, child security has become greater issue. Not only children even women has to be safeguard from threats. So, we are developing the smart wearable device for low cost which can be affordable for common people. To track the real-time location of the children, this project presents a mobile application where we have used Java, XML for code. This device is designed such that it monitors the child location and alerts the parents by sending SMS or voice message when the child moves out of the boundary. Even though using Wifi and Bluetooth, many systems are there for security purpose. This paper describes the system which comprises of an MPU 6050 gyroscope, Node MCU microcontroller and other sensors, GPS receiver for smart and safe usage. This includes some characteristics of high reliability, efficiency, short response time, high accuracy. The requirements enable to child's safety.

Extensive Support System and Knowledge Base for Improvised Geoponics Using Convolutional Neural Network Based Deep Learning

2020 ◽  
Vol 17 (8) ◽  
pp. 3437-3443
Author(s):  
S. Visnu Dharsini ◽  
Arpan Sarkar ◽  
Aritra Paul ◽  
Pranab Kumar Shukla
Keyword(s):  
Feedback Loop ◽  
Growth Form ◽  
Great Effort ◽  
Similar Model ◽  
Location Data ◽  
Fine Grain ◽  
Current Growth ◽  
Multistep Process ◽  
Crop Damages ◽  
Identification Model

Farming can either be envisaged as a complex multistep process or a linear and recursive feedback loop. In both cases, it requires great effort and cost to produce crops initially. Farmers have extensive knowledge about the crop they are growing, and they must know about the product, but sometimes it so happens that the farmers do not have at par and updated knowledge about the current growth form of the product. The loss per hectare of cultivation has been exponentially increasing over time due to extensive crop damages and failures. Our model suggests an overall algorithm to provide wholesome support and information to the producer may that be a farmer or someone who wishes to take up farming as a hobby. The CNN based model identifies the plant using fine-grain details like location data, timestamp, and state of harvest. Alongside the identification model, a similar model runs parallelly to identify any diseases that might be visible and also provides necessary steps to get rid of the same. Hence providing a safe and low-risk path towards mass producing a certain crop.

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