scholarly journals Functional dementia assessment using a video monitoring system: Proof of concept

2013 ◽  
Vol 10 (4) ◽  
Author(s):  
E. Mulin ◽  
V. Joumier ◽  
I. Leroi ◽  
J.H. Lee ◽  
J. Piano ◽  
...  
Keyword(s):  
Monitoring System ◽  
Video Monitoring ◽  
Proof Of Concept

An intelligent video-monitoring system to detect falls: a proof of concept

2018 ◽  
Vol 12 (4) ◽  
pp. 155-168
Author(s):  
Nolwenn Lapierre ◽  
Jean Meunier ◽  
Alain St-Arnaud ◽  
Jacqueline Rousseau
Keyword(s):  
Older Adults ◽  
Monitoring System ◽  
Detection System ◽  
Phase 1 ◽  
Fall Detection ◽  
Video Monitoring ◽  
False Alarms ◽  
Proof Of Concept ◽  
Content Type ◽  
At Home

Purpose To face the challenges raised by the high incidence of falls among older adults, the intelligent video-monitoring system (IVS), a fall detection system that respects privacy, was developed. Most fall detection systems are tested only in laboratories. The purpose of this paper is to test the IVS in a simulation context (apartment-laboratory), then at home. Design/methodology/approach This study is a proof of concept including two phases: a simulation study to test the IVS in an apartment-laboratory (29 scenarios of activities including falls); and a 28-day pre-test at home with two young occupants. The IVS’s sensitivity (Se), specificity (Sp), accuracy (A) and error rate (E) in the apartment-laboratory were calculated, and functioning at home was documented in a logbook. Findings For phase 1, results are: Se =91.67 per cent, Sp =99.02 per cent, A=98.25 per cent, E=1.75. For phase 2, the IVS triggered four false alarms and some technical dysfunctions appeared (e.g. computer screen never turning off) that are easily overcome. Practical implications Results show the IVS’s efficacy at automatically detecting falls at home. Potential issues related to future installation in older adults’ homes were identified. This proof of concept led to recommendations about the installation and calibration of a camera-based fall detection system. Originality/value This paper highlights the potentialities of a camera-based fall detection system in real-world contexts and supports the use of the IVS to help older adults age in place.

scholarly journals COVIMOS: A Coastal Video Monitoring System

2017 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
I Made Oka Widyantara ◽  
I Made Dwi Asana Putra ◽  
Ida Bagus Putu Adnyana
Keyword(s):  
Monitoring System ◽  
Nearest Neighbor ◽  
Low Cost ◽  
Video Image ◽  
Video Monitoring ◽  
Reference Object ◽  
Self Organizing Map ◽  
K Nearest Neighbor ◽  
Ip Camera ◽  
Class Labels

This paper intends to explain the development of Coastal Video Monitoring System (CoViMoS) with the main characteristics including low-cost and easy implementation. CoViMoS characteristics have been realized using the device IP camera for video image acquisition, and development of software applications with the main features including detection of shoreline and it changes are automatically. This capability was based on segmentation and classification techniques based on data mining. Detection of shoreline is done by segmenting a video image of the beach, to get a cluster of objects, namely land, sea and sky, using Self Organizing Map (SOM) algorithms. The mechanism of classification is done using K-Nearest Neighbor (K-NN) algorithms to provide the class labels to objects that have been generated on the segmentation process. Furthermore, the classification of land used as a reference object in the detection of costline. Implementation CoViMoS system for monitoring systems in Cucukan Beach, Gianyar regency, have shown that the developed system is able to detect the shoreline and its changes automatically.

scholarly journals Low-Cost and Energy-Saving Wireless Sensor Network for Real-Time Urban Mobility Monitoring System

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Joyoung Lee ◽  
Zijia Zhong ◽  
Bo Du ◽  
Slobodan Gutesa ◽  
Kitae Kim
Keyword(s):  
Energy Saving ◽  
Fiber Optics ◽  
Monitoring System ◽  
Data Center ◽  
Low Cost ◽  
Wireless Sensor ◽  
Navigation Systems ◽  
Urban Mobility ◽  
Proof Of Concept ◽  
Sensor Unit

This paper presents a low-cost and energy-saving urban mobility monitoring system based on wireless sensor networks (WSNs). The primary components of the proposed sensor unit are a Bluetooth sensor and a Zigbee transceiver. Within the WSN, the Bluetooth sensor captures the MAC addresses of Bluetooth units equipped in mobile devices and car navigation systems. The Zigbee transceiver transmits the collected MAC addresses to a data center without any major communications infrastructures (e.g., fiber optics and 3G/4G network). A total of seven prototype sensor units have been deployed on roadway segments in Newark, New Jersey, for a proof of concept (POC) test. The results of the POC test show that the performance of the proposed sensor unit appears promising, resulting in 2% of data drop rates and an improved Bluetooth capturing rate.

Research of Bus Video Monitoring System Based on WCDMA

2014 ◽  
Vol 543-547 ◽  
pp. 891-894
Author(s):  
Lian Jun Zhang ◽  
Shi Jie Liu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Transmission System ◽  
Video Data ◽  
Video Monitoring ◽  
Video Server ◽  
Real Time Transmission ◽  
Monitoring Center ◽  
Server System ◽  
Transmission Ability

The bus video monitoring system is composed by WCDMA transmission system, video server system, system monitoring center and outreach system. By WCDMA wireless transmission module achieving real time video data return, while using VPDN network technology. Using of the DVS video server and by WCDMA transmission system, the monitoring videos information will be transmitted to the monitoring center rapidly and in real time. The monitoring center can remotely monitor, manage, and dispatch the bus. The results demonstrating this system has good real time transmission ability.

scholarly journals A Multiobjective Piglet Image Segmentation Method Based on an Improved Noninteractive GrabCut Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Feilong Kang ◽  
Chunguang Wang ◽  
Jia Li ◽  
Zheying Zong
Keyword(s):  
Image Segmentation ◽  
Real Time ◽  
Monitoring System ◽  
Structural Similarity ◽  
Morphological Processing ◽  
Video Monitoring ◽  
Segmentation Method ◽  
Time Requirements ◽  
And Behavior ◽  
Grabcut Algorithm

In the video monitoring of piglets in pig farms, study of the precise segmentation of foreground objects is the work of advanced research on target tracking and behavior recognition. In view of the noninteractive and real-time requirements of such a video monitoring system, this paper proposes a method of image segmentation based on an improved noninteractive GrabCut algorithm. The functions of preserving edges and noise reduction are realized through bilateral filtering. An adaptive threshold segmentation method is used to calculate the local threshold and to complete the extraction of the foreground target. The image is simplified by morphological processing; the background interference pixels, such as details in the grille and wall, are filtered, and the foreground target marker matrix is established. The GrabCut algorithm is used to split the pixels of multiple foreground objects. By comparing the segmentation results of various algorithms, the results show that the segmentation algorithm proposed in this paper is efficient and accurate, and the mean range of structural similarity is [0.88, 1]. The average processing time is 1606 ms, and this method satisfies the real-time requirement of an agricultural video monitoring system. Feature vectors such as edges and central moments are calculated and the database is well established for feature extraction and behavior identification. This method provides reliable foreground segmentation data for the intelligent early warning of a video monitoring system.

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