Olivia Duong, Justin Crew, Jason Rea, Sasan Haghani, Maria Striki
{"title":"A Multi-Functional Drone for Agriculture Maintenance and Monitoring in Small-Scale Farming","authors":"Olivia Duong, Justin Crew, Jason Rea, Sasan Haghani, Maria Striki","doi":"10.1109/ICCE59016.2024.10444489","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444489","url":null,"abstract":"Agriculture covers almost 40% of the Earth’s land surface and is essential to human survival. Farmers, however, face numerous challenges to maintain sustainable production. This work introduces an innovative, low cost and comprehensive solution to address some of these challenges. We designed and implemented a multi-functional agricultural drone with monitoring tasks to ensure crops are adequately watered, protected from pests, and monitored for fires. Our results show the potential to improve the effectiveness of small-scale farming operations.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"1 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Communication Quality Measurement with Real Machines of AMR Ad Hoc Network on Optimal Route Movement","authors":"Risa Takeuchi, Tutomu Murase","doi":"10.1109/ICCE59016.2024.10444404","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444404","url":null,"abstract":"In this study, we will verify whether the relay node travel route control method is effective in actual experiments. When an Autonomous Mobile Robot (AMR) requires high-throughput wireless LAN communication during its travel, a system has been proposed to configure an ad hoc network that uses other AMRs (hereafter referred to as nodes) for data relay. Optimal routing control methods have already been proposed to enable relay nodes that relay data to communicate at high throughput. The proposed control method uses a computational model with a simple function, and its effectiveness has been demonstrated. However, the issue is to verify the effectiveness in a real communication environment. Therefore, we conducted experiments on actual equipment and compared the calculated results with the experimental results on actual equipment. The difference between the calculated results and the actual environment was limited to 18 points at most. Therefore, we have shown that the proposed path control method is effective.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"110 7","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improve Fine-grained Visual Classification Accuracy by Controllable Location Knowledge Distillation","authors":"You-Lin Tsai, Cheng-Hung Lin, Po-Yung Chou","doi":"10.1109/ICCE59016.2024.10444242","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444242","url":null,"abstract":"The current state-of-the-art network models have achieved remarkable performance. However, they often face an issue of having excessively large architectures, making them challenging to deploy on edge devices. In response to this challenge, a groundbreaking solution known as knowledge distillation has been introduced. The concept of knowledge distillation involves transferring information from a complex teacher model to a simpler student model, effectively reducing the model’s complexity. Prior approach has demonstrated promising transfer effects through this technique. Nevertheless, in the field of fine-grained image classification, there has been limited exploration of distillation methods custom-tailored specifically for this domain. In this paper, we focus on knowledge distillation specifically designed for fine-grained image recognition. Notably, this strategy is inspired by the Class Activation Maps (CAM). We first train a complex model and use it generated feature maps with spatial information, which is call hint maps. Furthermore, we propose an adjustment strategy for this hint map, which can control local distribution of information. Referring to it as Controllable Size CAM (CTRLS-CAM). Use it as a guide allowing the student model to effectively learn from the teacher model’s behavior and concentrate on discriminate details. In contrast to conventional distillation models, this strategy proves particularly advantageous for fine-grained recognition, enhancing learning outcomes and enabling the student model to achieve superior performance. In CTRLS-CAM method, we refine the hint maps value distribution, redefining the relative relationships between primary and secondary feature areas. We conducted experiments using the CUB200-2011 dataset, and our results demonstrated a significant accuracy improvement of about 5% compared to the original non-distilled student model. Moreover, our approach achieved a 1.23% enhancement over traditional knowledge distillation methods.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"96 11","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Color Electronic Paper with Front Light","authors":"Wen-Chung Kao, Yi-Cheng Hsu, Kai-Dun Hong, Ren-Xiang Ying","doi":"10.1109/ICCE59016.2024.10444423","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444423","url":null,"abstract":"The color electronic paper (CEP) can be realized by printing color inks on a black/white electrophoretic display. However, the overall lightness will be significantly reduced. A good solution to this issue is to equip it with a front light panel to enhance the overall brightness and colorfulness. This paper presents a color reproduction system for this new CEP. Comprehensive approaches to color gamut estimation, best front light selection, and gamut mapping for various front light settings are presented.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"25 3","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Timing offset independent PSCCH detection method for 5G-NR V2X SL systems","authors":"Jonggyu Oh, Kiyoung Kwak, Kangmin Lee","doi":"10.1109/ICCE59016.2024.10444353","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444353","url":null,"abstract":"In this paper, timing offset (TO) independent physical sidelink control channel (PSCCH) power and orthogonal cover code (OCC) index detection method for 5G new radio (NR) vehicle-to-everything (V2X) sidelink (SL) system is proposed. By employing normalized differential correlation and phase correction, the presence of PSCCH and transmitted OCC index detection are achieved regardless of TO.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"16 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Possibilities of AI and Augmented Reality in Education","authors":"F. Gelana, Abraham Campbell","doi":"10.1109/ICCE59016.2024.10444487","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444487","url":null,"abstract":"Current advancements in Artificial Intelligence (AI), especially in the field of Generative AI where Large Language Models such as GPT4, Bard, LLaMA, that are trained on large sum of human knowledge (Internet) open a great opportunity to revolutionize education. One way that AI and Augmented Reality (AR) can be used in education is to create personalized learning experiences for students, especially for STEM subjects. With the possibility of capable AR hardware that has powerful computing chips such as Apple’s vision, students can have a more immersive and interactive learning experience. Additionally, the rise of open-source language models such as LLaMa can help democratize access to AI and AR technologies for educational purposes.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"12 7","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antonio Nocera, Gianluca Ciattaglia, Michela Raimondi, Linda Senigagliesi, E. Gambi
{"title":"Identification of Smartphone Zombies and Normal Pedestrians Using FMCW Radar and Machine Learning","authors":"Antonio Nocera, Gianluca Ciattaglia, Michela Raimondi, Linda Senigagliesi, E. Gambi","doi":"10.1109/ICCE59016.2024.10444294","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444294","url":null,"abstract":"Mobile phone usage represents a source of distraction for pedestrians, who are losing awareness of external hazards given by vehicles and environment. Radars could be a solution to monitor continuously and privately the behaviours of pedestrians in the main public spaces in order to find solutions based on the way pedestrians walk, their habits and their walking speed. Being able to identify a pedestrian with the head down on the phone, usually called “smartphone zombie’’, is crucial to intervene to make the road safer and discourage the behaviour. We study the feasibility of identifying the walking pattern of “smartphone zombie’’ against a control pedestrian walking normally exploiting an automotive frequency modulated continuous wave radar working at 77 GHz. By applying principal component analysis and machine learning we obtain a classification accuracy of 92.4% of smartphone zombies against normal walk and 87.6% when adding a third class of fast walkers.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"11 6","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Layth Hamad, Muhammad Asif Khan, H. Menouar, F. Filali, Amr Mohamed
{"title":"Haris: an Advanced Autonomous Mobile Robot for Smart Parking Assistance","authors":"Layth Hamad, Muhammad Asif Khan, H. Menouar, F. Filali, Amr Mohamed","doi":"10.1109/ICCE59016.2024.10444311","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444311","url":null,"abstract":"This paper presents Haris, an advanced autonomous mobile robot system for tracking the location of vehicles in crowded car parks using license plate recognition. The system employs simultaneous localization and mapping (SLAM) for autonomous navigation and precise mapping of the parking area, eliminating the need for GPS dependency. In addition, the system utilizes a sophisticated framework using computer vision techniques for object detection and automatic license plate recognition (ALPR) for reading and associating license plate numbers with location data. This information is subsequently synchronized with a back-end service and made accessible to users via a user-friendly mobile app, offering effortless vehicle location and alleviating congestion within the parking facility. The proposed system has the potential to improve the management of short-term large outdoor parking areas in crowded places such as sports stadiums. The demo of the robot can be found on https://youtu.be/ZkTCM35fxa0?si = QjggJuN7M1o3oifx.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"71 11","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ChatGPT: A Companion for Dementia Care","authors":"Gahangir Hossain, Znaida Simpson Pomare, Gayle Prybutok","doi":"10.1109/ICCE59016.2024.10444253","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444253","url":null,"abstract":"Dementia is characterized by the progressive degeneration of the brain, resulting in cognitive impairment and disruptions in neurological functioning. Various factors, including traumatic events, stress-related conditions, or post-stroke brain damage, contribute to its onset. While dementia lacks a cure, there are reversible interventions to manage its effects, enabling individuals to age successfully with cognitive support from assistive technologies like ChatGPT. Recent study highlighted the benefits of ChatGPT in aiding memory acquisition for individuals experiencing cognitive decline, which can be applied in providing companionship to older adults dealing with dementia. As the innovative application of artificial intelligence (AI), ChatGPT in the form of medical chatbot, can address feelings of loneliness, and foster essential social interaction. In summary, ChatGPT's use offers cognitive support and enhances the overall well-being of those facing cognitive decline.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"86 11","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tutomu Murase, Yukinobu Fukushima, Celimuge Wu, Yusheng Ji
{"title":"Multi-stage Information Processing Systems with VM Migration for Maximum Accuracy","authors":"Tutomu Murase, Yukinobu Fukushima, Celimuge Wu, Yusheng Ji","doi":"10.1109/ICCE59016.2024.10444232","DOIUrl":"https://doi.org/10.1109/ICCE59016.2024.10444232","url":null,"abstract":"This paper outlines a Multi-stage Information Processing system and a VM migration method to improve the performance of the system. To process applications that require responsiveness and accuracy at the same time, such as sensor data processing in automated driving, a Multi-stage Information Processing system has been proposed in which the edge computer and the data center computer process information simultaneously to obtain responsiveness from the edge computer and accuracy from the data center. This paper describes the system and explains the VM migration method to obtain highly accurate responsiveness in such a system.","PeriodicalId":518694,"journal":{"name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","volume":"78 5","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}