{"title":"A cloud-based middleware for multi-modal interaction services and applications","authors":"Bilgin Avenoglu, V. J. Koeman, K. Hindriks","doi":"10.3233/ais-220161","DOIUrl":null,"url":null,"abstract":"Smart devices, such as smart phones, voice assistants and social robots, provide users with a range of input modalities, e.g., speech, touch, gestures, and vision. In recent years, advancements in processing of these input channels enable more natural interaction (e.g., automated speech, face, and gesture recognition, dialog generation, emotion expression etc.) experiences for users. However, there are several important challenges that need to be addressed to create these user experiences. One challenge is that most smart devices do not have sufficient computing resources to execute the Artificial Intelligence (AI) techniques locally. Another challenge is that users expect responses in near real-time when they interact with these devices. Moreover, users also want to be able to seamlessly switch between devices and services any time and from anywhere and expect personalized and privacy-aware services. To address these challenges, we design and develop a cloud-based middleware (CMI) which helps to develop multi-modal interaction applications and easily integrate applications to AI services. In this middleware, services developed by different producers with different protocols and smart devices with different capabilities and protocols can be integrated easily. In CMI, applications stream data from devices to cloud services for processing and consume the results. It supports data streaming from multiple devices to multiple services (and vice versa). CMI provides an integration framework for decoupling the services and devices and enabling application developers to concentrate on “interaction” instead of AI techniques. We provide simple examples to illustrate the conceptual ideas incorporated in CMI.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"20 1","pages":"455-481"},"PeriodicalIF":1.8000,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ambient Intelligence and Smart Environments","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.3233/ais-220161","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Smart devices, such as smart phones, voice assistants and social robots, provide users with a range of input modalities, e.g., speech, touch, gestures, and vision. In recent years, advancements in processing of these input channels enable more natural interaction (e.g., automated speech, face, and gesture recognition, dialog generation, emotion expression etc.) experiences for users. However, there are several important challenges that need to be addressed to create these user experiences. One challenge is that most smart devices do not have sufficient computing resources to execute the Artificial Intelligence (AI) techniques locally. Another challenge is that users expect responses in near real-time when they interact with these devices. Moreover, users also want to be able to seamlessly switch between devices and services any time and from anywhere and expect personalized and privacy-aware services. To address these challenges, we design and develop a cloud-based middleware (CMI) which helps to develop multi-modal interaction applications and easily integrate applications to AI services. In this middleware, services developed by different producers with different protocols and smart devices with different capabilities and protocols can be integrated easily. In CMI, applications stream data from devices to cloud services for processing and consume the results. It supports data streaming from multiple devices to multiple services (and vice versa). CMI provides an integration framework for decoupling the services and devices and enabling application developers to concentrate on “interaction” instead of AI techniques. We provide simple examples to illustrate the conceptual ideas incorporated in CMI.
期刊介绍:
The Journal of Ambient Intelligence and Smart Environments (JAISE) serves as a forum to discuss the latest developments on Ambient Intelligence (AmI) and Smart Environments (SmE). Given the multi-disciplinary nature of the areas involved, the journal aims to promote participation from several different communities covering topics ranging from enabling technologies such as multi-modal sensing and vision processing, to algorithmic aspects in interpretive and reasoning domains, to application-oriented efforts in human-centered services, as well as contributions from the fields of robotics, networking, HCI, mobile, collaborative and pervasive computing. This diversity stems from the fact that smart environments can be defined with a variety of different characteristics based on the applications they serve, their interaction models with humans, the practical system design aspects, as well as the multi-faceted conceptual and algorithmic considerations that would enable them to operate seamlessly and unobtrusively. The Journal of Ambient Intelligence and Smart Environments will focus on both the technical and application aspects of these.