• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.1
• /
• pp.361-378
• /
• 2012

Most of the current frequency hopping (FH) based dynamic spectrum access (DSA) methods concern a reactive channel access scheme with synchronous inter-channel spectrum sensing, i.e., FH is reactively triggered by the primary user (PU)'s return reported by spectrum sensing, and the PU channel to be switched to is assumed precisely just sensed or ready to be sensed, as if the inter-channel spectrum sensing moments are synchronous. However, the inter-channel spectrum sensing moments are more likely to be asynchronous, which risks PU suffering more interference. Moreover, the spectrum sensing is usually erroneous, which renders the problem more complex. To address this problem, we propose a proactive FH based DSA method against both erroneous spectrum sensing and asynchronous inter-channel spectrum sensing (moments). We term it as proactive DSA. The optimal FH sequence is obtained by dynamic programming. The complexity is also analyzed. Finally, the simulation results confirm the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.7
• /
• pp.2212-2230
• /
• 2014

Cognitive radio (CR) users, known as secondary users (SUs), should avoid interference with primary users (PUs) who own the licensed band, while trying to access it; when the licensed band is unused by the PUs. To detect PUs, spectrum sensing should be performed over in-band channels that are currently in use by SUs. If PUs return to access the band, SUs need to vacate it, disrupting the SUs' communication unless a non-utilized band is discovered. Obtaining a non-utilized band in a short period facilitate seamless communication for SUs and avoid interference on PUs by vacating from the channel immediately. Searching for a non-utilized band can be done through proactive out-of-band (OB) sensing. In this paper, we suggest a proactive OB sensing scheme that minimizes the time required to discover a non-utilized spectrum in order to continue communication. Although, the duration spent on OB sensing reduces the throughput of the CR networks that can be achieved on band being utilized, the lost throughput can be compensated in the new discovered band. We demonstrate that, the effect of our proposed scheme on the throughput owing to OB sensing is insignificant, while exhibiting a very short channel discovery time.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.52
• /
• pp.171-180
• /
• 1999

Industrial equipment reliability improvement and maintenance is gaining attention as the next great opportunity for manufacturing productivity improvement. Reactive maintenance is expensive because of extensive unplanned downtime and damage to machinery. To avoid such an unplanned machine downtime, it is needed to use proactive maintenance approach by either using historical maintenance data or by sensing machine conditions. This paper discusses failure diagonosis and prediction based on the condition-based maintenance and reliability technique. Thus, by enabling such a framework, it can bring us more efficient planning and execution of maintenance to reduce costs and/or increase profits.

• Journal of the Korea Safety Management & Science
• /
• v.9 no.5
• /
• pp.79-85
• /
• 2007

Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal error. In order to proactive deal with these errors, a system which measures the temperature of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network based intelligent machine tools which look set to appear sooner or later.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.4
• /
• pp.959-979
• /
• 2024

Rice pest identification is essential in modern agriculture for the health of rice crops. As global rice consumption rises, yields and quality must be maintained. Various methodologies were employed to identify pests, encompassing sensor-based technologies, deep learning, and remote sensing models. Visual inspection by professionals and farmers remains essential, but integrating technology such as satellites, IoT-based sensors, and drones enhances efficiency and accuracy. A computer vision system processes images to detect pests automatically. It gives real-time data for proactive and targeted pest management. With this motive in mind, this research provides a novel farmland fertility algorithm with a deep learning-based automated rice pest detection and classification (FFADL-ARPDC) technique. The FFADL-ARPDC approach classifies rice pests from rice plant images. Before processing, FFADL-ARPDC removes noise and enhances contrast using bilateral filtering (BF). Additionally, rice crop images are processed using the NASNetLarge deep learning architecture to extract image features. The FFA is used for hyperparameter tweaking to optimise the model performance of the NASNetLarge, which aids in enhancing classification performance. Using an Elman recurrent neural network (ERNN), the model accurately categorises 14 types of pests. The FFADL-ARPDC approach is thoroughly evaluated using a benchmark dataset available in the public repository. With an accuracy of 97.58, the FFADL-ARPDC model exceeds existing pest detection methods.

• Journal of Animal Science and Technology
• /
• v.66 no.1
• /
• pp.31-56
• /
• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.16 no.1
• /
• pp.120-130
• /
• 2012

As long span and complex bridges are constructed often recently, safety estimation became a big issue. Various types of measuring instruments are installed in case of long span bridge. New wireless technologies for long span bridges such as sending information through a gateway at the field or sending it through cables by signal processing the sensing data are applied these days. However, The case of occurred accidents related to bridge in the world have been reported that serious accidents occur due to lack of real-time proactive, intelligent action based on recognition accidents. To solve this problem in this study, the idea of "communication among things", which is the basic method of RFID/USN technology, is applied to the bridge monitoring system. A sensor node module for USN based intelligent bridge system in which sensor are utilized on the bridge and communicates interactively to prevent accidents when it captures the alert signals and urgent events, sends RF wireless signal to the nearest traffic signal to block the traffic and prevent massive accidents, is designed and tested by performing TinyOS based middleware design and sensor test free Space trans-receiving distance.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.2B
• /
• pp.98-106
• /
• 2006

In order to provide a realtime transmission over a wireless LAM, we here present a new jamming based retransmission mechanism. In a legacy wireless LAN system, all stations use the binary exponential backoff algorithm to avoid collisions among frames. It is well known that the backoff algorithm causes more collisions as the numbers of active stations increases. This makes transmission of real time traffic hard. In the proposed scheme, when each station senses collisions, it promptly allows to send a jamming signal during a unique jamming window period which is determined by its own channel access count database(CACDB). This jamming windows is chosen not to be overlapped each other by using of CACDB, and thus channel access of another station is prevented. Hereafter the station gets the ownership of the medium when the wireless medium becomes idle after sending the jamming signal and sensing carrier, and then sends frame in medium. In our proposal, repeating collisions is never happened. We here assume that real time traffic use a frame of fixed length in order to make the time for receiving its ACK frame same. Comparing the proposed jamming-based retransmission scheme with the the 802.11 and 802.11e MAC by simulation. one can find that the proposed scheme have advantages in terms of delay, average backoff time, and average number of collisions per frame. One can find that the proposed scheme might be practically applicable to several applications of realtime traffic transmission in wireless LAN systems.