• Journal of Engineering Education Research
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• v.13 no.5
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• pp.76-80
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• 2010

In this paper, the Location Compensation Mechanism using equivalent distance rate ($LCM_{edr}$) for localization system based on SDS-TWR (Symmetric Double-Sided Two-Way Ranging) in wireless sensor network is proposed. The performance of the mechanism is experimented in terms of two types of the localization tracking scenarios of indoor and outdoor environments in university campus. From the experimentations, the compensation ratio in the $LCM_{edr}$ is better than that in SDS-TWR about 90% in indoor/outdoor environments in scenario 1 but also is better than that of SDS-TWR about 91.7% in indoor environment and about 100% in outdoor environment in scenario 2 respectively.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.1-8
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• 2016

Current indoor intrusion detection and location tracking methods have the weakness in seamless operations in tracking the objective because the object must possess a communicating device and the limitation of the single cell size (approximate $100cm{\times}100cm$) exits. Also, the utilization of CCTV technologies show the shortcomings in tracking when the object disappear the area where the CCTV is not installed or illumination is not enough for capturing the scene (e.g. where the context-awarded system is not installed or low illumination presents). Therefore, in this paper we present an improved in-door tracking system based on sensor networks. Such system is built on a simulated scenario and enables us to detect and extend the area of surveillance as well as actively responding the emergency situation. Through simulated studies, we have demonstrated that the proposed system is capable of supplementing the shortcomings of signal cutting, and of estimating the location of the moving object. We expect the study will improve the better analysis of the intruder behavior, the more effective prevention and flexible response to various emergency situations.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.329-334
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• 2011

This paper presents the method for location estimation with obstacle tracking method. A laser scanner is used to implement the system, and we assume that the map information is known. We matches the measurement of the laser scanner to estimate the location of the robot by using sequential monte carlo (SMC) method. After estimating the robot's location, the pose of obstacles are detected and tracked, hence, we can predict the collision risk of them. Finally, we present the experiment results to verify the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4408-4428
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• 2019

Due to the rapid advancement in smart phones, numerous new specifications are developed for variety of applications ranging from health monitoring to navigations and tracking. The word indoor navigation means location identification, however, where GPS signals are not available, accurate indoor localization is a challenging task due to variation in the received signals which directly affect distance estimation process. This paper proposes a hybrid approach which integrates fingerprinting based K-Nearest Neighbors (K-NN) and lateration based MinMax position estimation technique. The novel idea behind this hybrid approach is to use Euclidian distance formulation for distance estimates instead of indoor radio channel modeling which is used to convert the received signal to distance estimates. Due to unpredictable behavior of the received signal, modeling indoor environment for distance estimates is a challenging task which ultimately results in distance estimation error and hence affects position estimation process. Our proposed idea is indoor position estimation technique using Bluetooth enabled smart phones which is independent of the radio channels. Experimental results conclude that, our proposed hybrid approach performs better in terms of mean error compared to Trilateration, MinMax, K-NN, and existing Hybrid approach.

• IE interfaces
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• v.25 no.1
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• pp.114-126
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• 2012

This study describes a real-time location monitoring system developed for efficient operation of workplace in plant equipment maker. This monitoring system can be applied for indoor and outdoor working environment respectively. By using the real-time tracking system based on RTLS, it is possible to track worker's movement and location of working object under indoor working environment. For outdoor working environment, the real-time monitoring system based on IDGPS is applied for work safety and balanced workload. A case study is provided to evaluate the performance of the real-time monitoring system.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.81-84
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• 2007

In this research, we will accomplish the investigation of the devices and data models which are used in the existing indoor and outdoor systems. Based on the investigation, we will seize the additional requirements for the integration of the legacy system and then we will propose the various methods which support the additional requirements. By applying the various methods in the heterogeneous environments, we will solve the legacy problems and propose the methods for the final goal that is to provide the seamless moving object tracking. The scope of this research is to propose the integration methods, developing the actual location tracking system model without modifying the legacy infrastructures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1856-1869
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• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.537-542
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• 2008

Cricket is an excellent indoor location system and it can successfully solve many critical problems such as user privacy, decentralized administration. But in some practical applications, Cricket sometimes didn't provide location with enough accuracy, and was unable to determine when it was giving inaccurate information. For getting high-accuracy tracking performance from location data contaminated with noise, some types of filters are required. Kalman Filter is an efficient recursive filter that estimates the state of a dynamic system from a series of incomplete and noisy measurement. The filter is very powerful in the field of autonomous and assisted navigation. In this paper, we carry out comparative studies to validate the performance of the application of Kalman Filter to Cricket based localization system.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.16-23
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• 2019

Fine particulate matter known as PM 2.5 refers to the atmospheric particulate matter that has a diameter less than 2.5 micrometer identified as dangerous element for human health and its concentration can provide us a clear picture about air dust concentration. Humans stay indoor almost 90% of their life time and also there is no official indoor dust concentration data, so our study is focused on measuring the indoor air quality. Indoor dust data monitoring is very important in hospital environments beside that other places can also be considered for monitoring like classrooms, cements factories, computer server rooms, petrochemical storage etc. In this paper, visible light communication system is proposed by Manchester encoding technique for electromagnetic interference (EMI)-free indoor dust monitoring. Important indoor environment information like dust concentration is transferred by visible light channel in wide range. An average voltage-tracking technique is utilized for robust light detection to eliminate ambient light and low-frequency noise. The incoming light is recognized by a photo diode and are simultaneously processed by a receiver micro-controller. We can monitor indoor air quality in real-time and can take necessary action according to the result.

• Journal of information and communication convergence engineering
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• v.5 no.4
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• pp.382-388
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• 2007

Indoor location system using wireless sensor network technology was applied for the status evaluation and activity monitoring of elderly person or chronic invalid at home. Location awareness application is transparent to the daily activities, while providing the embedded computing infrastructure with an awareness of what is happening in this space. To locate an object, the active ceiling-mounted reference beacons were placed throughout the building. Reference beacons periodically publish location information on RF and ultrasonic signals to allow application running on mobile or static nodes to study and determine their physical location. Once object-carried passive listener receives the information, it subsequently determines it's location from reference beacons. By using only the sensor nodes without any external network infrastructure the cost of the system was reduced while the accuracy in our experiments. was fairly good and fine grained between 7 and 15 cm for location awareness in indoor environments. Passive architecture used here provides the security of the user privacy while at the server the privacy was secured by providing the authentication using Geopriv approach. This information from sensor nodes is further forwarded to base station where further computation is performed to determine the current position of object and several applications are enabled for context awareness.