[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-647319-105":3,"detail-sidebar-cat-0-en-105":80,"doc-detail-647319-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":73,"head_meta":75,"extra_data":77,"updated_unix":79},105,"en","autobridge-automating-iot-integration-code-generation","AutoBridge - Automating IoT Integration Code Generation","","Multimodal IoT systems coordinate diverse IoT devices to deliver human-centered services, and they must support adding new devices under a centralized platform. The task is difficult because developers need substantial expertise to implement complex integration code that lets the platform understand and control device functions. AutoBridge automates integration-code generation using divide-and-conquer logic, platform-compliant synthesis, and a multi-stage debugging pipeline.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/autobridge-automating-iot-integration-code-generation/647319/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/autobridge-automating-iot-integration-code-generation/647319.png","ImageObject",300,407,{"name":42,"@type":43},"Quinn Holloway","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-27","2026-10-23",true,{"@type":52,"interactionType":53,"userInteractionCount":26},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"What problem does AutoBridge address in multimodal IoT systems?","Question",{"text":62,"@type":63},"AutoBridge addresses the difficulty of generating IoT integration code when new devices are added to a centralized platform. It targets the human effort required to program platform-understandable control logic for device functions.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"How does AutoBridge generate integration code?",{"text":67,"@type":63},"AutoBridge uses a divide-and-conquer strategy: it first generates device control logic by progressively retrieving device-specific knowledge, then synthesizes platform-compliant integration code using platform-specific knowledge.",{"name":69,"@type":60,"acceptedAnswer":70},"What debugging approach does AutoBridge use to ensure correctness?",{"text":71,"@type":63},"AutoBridge uses a multi-stage debugging pipeline with an automated debugger for virtual IoT device testing and an interactive hardware-in-the-loop debugger that only requires binary (“yes/no”) user feedback for real-device verification.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},647319,1793115352,{"code":4,"msg":81,"data":82},"success",[83,87,91,95,100,105,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":84,"show_sort_weight":85,"slug":86},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":88,"show_sort_weight":89,"slug":90},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":92,"show_sort_weight":93,"slug":94},"Exam",70,"exam",{"id":96,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},5,"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},8,30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":96,"slug":129},19,"General","general",{"code":4,"msg":81,"data":131},{"doc_id":78,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":111,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":26,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145},2336474466712,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","AutoBridge: Automating Smart Device Integration with  \nCentralized Platform  \nSiyuan Liu  \n[sliu268@connect.hkust-gz.edu.cn](sliu268@connect.hkust-gz.edu.cn)[ ](sliu268@connect.hkust-gz.edu.cn)Hong Kong University of Science and Technology (Guangzhou) Guangzhou, Guangdong, China  \nZhice Yang  \n[yangzhc@shanghaitech.edu.cn](yangzhc@shanghaitech.edu.cn)[ ](yangzhc@shanghaitech.edu.cn)ShanghaiTech University Shanghai, China  \nHuangxun Chen  \n[huangxunchen@hkust-gz.edu.cn](huangxunchen@hkust-gz.edu.cn)[ ](huangxunchen@hkust-gz.edu.cn)Hong Kong University of Science and Technology (Guangzhou) Guangzhou, Guangdong, China  \narXiv :2507 .23 178v 1 [ cs . SE] 31 Jul 2025  \nAbstract  \nMultimodal IoT systems coordinate diverse IoT devices to deliver human-centered services. The ability to incorporate new IoT devices under the management of a centralized platform is an essential requirement. However, it requires significant human expertise and effort to program the complex IoT integration code that enables the platform to understand and control the device’s functions. Therefore, we propose AutoBridge to automate IoT integration code generation. Specifically, AutoBridge adopts a divide-and-conquer strategy: it first generates device control logic by progressively retrieving device-specific knowledge, then synthesizes platformcompliant integration code using platform-specific knowledge. To ensure correctness, AutoBridge features a multi-stage debugging pipeline, including an automated debugger for virtual IoT device testing and an interactive hardware-in-the-loop debugger that requires only binary user feedback (“yes/no”) for real-device verification. We evaluate AutoBridge on a benchmark of 34 IoT devices across two open-source IoT platforms. The results demonstrate that AutoBridge can achieves an average success rate of 93.87% and an average function coverage of 94.87%, without any human involvement. With minimal binary \"yes/no\" feedback from users, the code is then revised to reach 100% function coverage. A user study with 15 participants further shows that AutoBridge outperforms expert programmers by 50%–80% in code accuracy, even when the programmers are allowed to use commercial code LLMs.  \nCCS Concepts  \n• Human-centered computing → Ubiquitous and mobile computing systems and tools; Natural language interfaces.  \nKeywords  \nIoT Management, Large Language Model, IoT Program Synthesis  \n1 Introduction  \nOver the past few decades, IoTs have been widely integrated into everyday life. As illustrated in Figure 1, to serve human-centered needs, the IoT system encompasses multi-modal devices distributed throughout the space, with a centralized platform, e.g. [5, 34, 51] integrating all device control interfaces for unified coordination. However, no single device combination can satisfy all needs. Each user has unique requirements and budget constraints. These needs often evolve over time, leading to the addition or upgrade of devices within the space. A practical hurdle in incorporating a newly introduced device into the existing platform is the need to implement IoT  \nCorresponding Author: Huangxun Chen.  \nMulti-Modal IoT System for Human-centered Services  \nIncorporating New Devices under Centralized Management  \nProgrammer Code LLM AutoBridge  \nDomain Knowledge     \nCorrectness Guarantee     \nCompletion Efficiency     \nFigure 1: Personalized multi-modal IoT systems need to support dynamic upgrades and the addition of new IoT devices, which requires programming integration code to incorporate these devices with the centralized platform.  \nintegration code—custom code that is plugged into the centralized platform to help establish a connection with the device, retrieve data from it, and send control commands to it.  \nIn the past, we typically relied on programmers to implement integration code. However, this has proven to be a daunting task, as it requires gathering technical details from device documentation and understanding the platform","cbCaiiORejLPWgDV","https://ap.wps.com/l/cbCaiiORejLPWgDV","pdf",2464230,14,"English","# Introduction\n## Background of centralized IoT platforms\n## Motivation for automated integration code\n## Challenges in code LLM-based synthesis\n### CH1: Complexity of integration code\n### CH2: Heavy domain knowledge for integration","[{\"question\":\"What problem does AutoBridge address in multimodal IoT systems?\",\"answer\":\"AutoBridge addresses the difficulty of generating IoT integration code when new devices are added to a centralized platform. It targets the human effort required to program platform-understandable control logic for device functions.\"},{\"question\":\"How does AutoBridge generate integration code?\",\"answer\":\"AutoBridge uses a divide-and-conquer strategy: it first generates device control logic by progressively retrieving device-specific knowledge, then synthesizes platform-compliant integration code using platform-specific knowledge.\"},{\"question\":\"What debugging approach does AutoBridge use to ensure correctness?\",\"answer\":\"AutoBridge uses a multi-stage debugging pipeline with an automated debugger for virtual IoT device testing and an interactive hardware-in-the-loop debugger that only requires binary (“yes/no”) user feedback for real-device verification.\"}]","AutoBridge - Automating IoT Integration Code Generation | PDF",1792788268,35]