2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)最新文献_第2页

COVID Hotspot Alert System using Geo-Fencing Technique 基于地理围栏技术的COVID热点预警系统

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987296

D. Josephine, R. Shyam Sunder, S. Sharanesh, C. B. Nithin Ram, G. Hari Prasath

引用次数: 0

Automated Crack and Damage Identification in Premises using Aerial Images based on Machine Learning Techniques 基于机器学习技术的航拍图像的房屋裂纹和损伤自动识别

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987391

R. Prabu, G. Anitha, V. Mohanavel, M. Tamilselvi, G. Ramkumar

{"title":"Automated Crack and Damage Identification in Premises using Aerial Images based on Machine Learning Techniques","authors":"R. Prabu, G. Anitha, V. Mohanavel, M. Tamilselvi, G. Ramkumar","doi":"10.1109/I-SMAC55078.2022.9987391","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987391","url":null,"abstract":"The impartiality and reliability of evaluation, as well as the high time and expense demands, make it impossible to conduct a manual examination of infrastructure issues such as building fractures. For airborne images of damage, use unmanned aerial vehicles. Artificial intelligence and machine learning methods may help overcome the limits of many computer vision-based approaches to crack detection. But these hybrid approaches have their own limitations that can be solved. Images with damage may be more accurately detected using modified convolutional neural networks (MCNNs), which are less affected by picture noise. For fracture identification and damage assessment in civil infrastructures, a Modified Deep CNN Model (MDCNN) has been deployed. The 16-layer convolutional architecture and the Support Vector Machine are used in this design. The last layer of the CNN networks is replaced with SVM. Rather of relying on a single layer, we suggest a multi-layered network instead. Their abilities in identifying objects and putting them into categories are quite reliable. A further great benefit of MDCNNs is their ability to share the burden. When compared to a standard neural network, proposed method use significantly less processing power.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131984723","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}

引用次数: 8

Automatic Fish Detection in Underwater Videos using Machine Learning 利用机器学习在水下视频中自动检测鱼类

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987363

N. Radha, R. Swathika, P. Shreya

引用次数: 0

Artificial Intelligence and Advanced Technology based Bridge Safety Monitoring System 基于人工智能和先进技术的桥梁安全监测系统

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987328

D. Karunkuzhali, D. Geetha, G. Manikandan, J. Manikandan, V. Kavitha

{"title":"Artificial Intelligence and Advanced Technology based Bridge Safety Monitoring System","authors":"D. Karunkuzhali, D. Geetha, G. Manikandan, J. Manikandan, V. Kavitha","doi":"10.1109/I-SMAC55078.2022.9987328","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987328","url":null,"abstract":"In this study, wireless technology is used to provide a bridge security checking framework based on IoT. The robotized continuous scaffold wellness checking framework was developed with the assistance of breakthroughs in sensor technology. This method will help CEOs plan for and recover from disasters. The Wireless Technology is employed in the development of an IOT-based bridge security checking framework. Remote sensor hubs can collect several forms of data, such as vibration, water level, and bridge weight. These particulars would also be relevant for verification and observation. The primary purpose of this research is to develop a system that can detect and avoid flyover and extension mistakes, as well as underlying disasters. This study provides an overview of the various techniques used to screen the states of the scaffolds and proposes a framework for assessing constant designs as well as a water level sensor for monitoring the water level in the stream in order to keep traffic away from flood situations using AI calculations. If a crisis occurs, the Bridge’s doors will close as a result. The collected data is delivered to the server and data set, allowing managers to monitor the extension situation using portable telecom devices.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131607368","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}

引用次数: 0

Decentralized Pricing on Mobile Phone-based ESLs 基于手机的esl去中心化定价

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987339

Sandeep Shekhawat

引用次数: 5

Construction of Large-Scale Communication Network based on Abstract Extraction Algorithm 基于抽象提取算法的大规模通信网络构建

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987412

Chun Luo, Xianyong Wu, Zhicong Wu

引用次数: 0

Dense Captioning of Videos using Feature Context Integrated Deep LSTM with Local Attention 基于特征上下文集成深度LSTM和局部关注的视频密集字幕

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987416

J. Jacob, V. P. Devassia

{"title":"Dense Captioning of Videos using Feature Context Integrated Deep LSTM with Local Attention","authors":"J. Jacob, V. P. Devassia","doi":"10.1109/I-SMAC55078.2022.9987416","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987416","url":null,"abstract":"Dense captioning is a fast emerging area in video processing in natural language, that construe semantic contents present in an input video and. A traditional deep learning algorithm faces more challenges in solving this problem because it requires optimizing not just one set of values, but two sets, namely (1) event proposals, which are the timestamps for detecting an activity in a particular temporal region, and (2) natural language annotations for the detected proposals. Bidirectional LS TMs are used to predict event proposals based on information from the past and future of the event. Captions for detected events are also generated based on the past and future information associated with the event. The context vectors are augmented with original C3D video features in the decoder network in order to optimize the encoder network for proposals instead of captions. In this way, all the information necessary for the decoding network is provided. A local attention mechanism is added to the model so that it can focus on the relevant parts of the data to improve its performance. As a final step, captions will be generated with deep LSTMs. In order to verify the effectiveness of proposed model, a rigorous experiments have been conducted on the suggested innovations and demonstrated that it is remarkably effective at dense captioning events in videos with significant gains across a variety of metrics when it uses Feature Context Integrated (FC1) Deep LS TM with local attention.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133581001","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}

引用次数: 0

An Efficient and Secure Data Sharing Scheme for Ciphertext-Policy Attribute-based Signcryption for Cloud Storage Services 云存储服务中基于密文-策略属性签名加密的高效安全数据共享方案

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987411

V. Catherine, A. S. Nargunam

{"title":"An Efficient and Secure Data Sharing Scheme for Ciphertext-Policy Attribute-based Signcryption for Cloud Storage Services","authors":"V. Catherine, A. S. Nargunam","doi":"10.1109/I-SMAC55078.2022.9987411","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987411","url":null,"abstract":"In this paper, an efficient retrievable attribute with Ciphertext-policy attribute-based signcryption with accountable and verifiable outsourced designcryption (CP-ABSc-AVODs) was proposed towards enable sharing of data in cloud in a secure manner. The cloud provides accurate control on data access, encryption and authenticity to data for granting confidentiality and integrity to personal messages. This protocol enables signing of message, depending on the access privileges given in tree structure mentioned embedded with the message. Users will be able to decrypt to get plaintext if and only if they have the necessary properties satisfying the structure specified for data access. In addition, CP-ABSc-AVODs provide access policy update functionality to decrypt unsigned or signed cloud storage server messages and redistribute user secret keys. The feature of access policy update in CP-ABSc-AVODs has no effect on the number of messages or its size received at the client site and hence there is a reduction in bandwidth and memory usage. The proposed protocol includes general attack resistance, message detection, data protection and fraud prevention. In addition, the proposed method’s performance is evaluated by comparing with other methods with respect to size of the key, functionality and time required for computation.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133185160","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}

引用次数: 0

Embedded Color Segregation using Arduino 嵌入式颜色隔离使用Arduino

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987424

Sai Likhith Panuganti, Naseer Hussain Gajula, Prasanthi Rathnala, M.S. Pradeep Kumar Patnaik, Srinivasa Rao Sura

{"title":"Embedded Color Segregation using Arduino","authors":"Sai Likhith Panuganti, Naseer Hussain Gajula, Prasanthi Rathnala, M.S. Pradeep Kumar Patnaik, Srinivasa Rao Sura","doi":"10.1109/I-SMAC55078.2022.9987424","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987424","url":null,"abstract":"This research study proposes an embedded color segregation system using the multi-rate sensor data and color identification. There are plenty of applications for color segregation. The most prominent uses are for waste management and fruit and veg packing. In waste management, clutter is identified based on its size, shape and color. Sensor enabled color segregation helps to segregate the unwanted items with ease of use. Another application is segregating the available fruit and veg from the agricultural produce. One of best approaches to achieve this is based on its color, which is the most economical and fast method. The idea of this color segregation is to extend the work further to develop an autonomous waste management system. The proposed prototype segregates color category based on sensor measurements collected from RGB sensor, TCS34725. Segregating color is very simple to human eyes, but there are a lot of background tasks for a sensor to detect the actual given color. TCS34725 detects the color and makes human life easier by providing the exact RGB values, which cannot be identified by the naked eye. A test methodology has been followed to validate the proposed segregation approach. To perform this, a real time prototype has been developed and measured around 10k samples under different conditions. Results indicate that the proposed approach has achieved significant benefits, i.e., accuracy is above 95%, response time less than 3ms.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115994996","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}

引用次数: 1

PID Controller based on BP Neural Network for Speed Control of Electric Vehicle 基于BP神经网络的电动汽车速度PID控制

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987364

Shannmukha Naga Raju Vonteddu, P. Nunna, P. Subramanian, V. Gopu, M. Nagarajan, G. Diwakar

引用次数: 0