The Microverse: A Task-Oriented Edge-Scale Metaverse This paper introduces the microverse, a task-oriented, edge-scale solution for smart cities, designed to address the challenges of integrating smart city technologies such as IoT, edge-fog-cloud computing, and AI. The microverse is a digital twin of an individual network slice, enabling on-site/near-site data processing, information fusion, and real-time decision-making within the edge-fog-cloud computing framework. Unlike all-encompassing metaverses, each microverse instance serves a specific task as a manageable digital twin of an individual network slice. The microverse concept is verified using smart public safety surveillance (SPSS) for smart communities as a case study, demonstrating its feasibility in practical smart city applications. The paper discusses the challenges of integrating the metaverse with IoT, including bandwidth and latency constraints, scalability, interoperability, security, and privacy. It also explores the enabling technologies of the metaverse, including digital twins, network slicing, and lightweight blockchain. The microverse framework is proposed as a hierarchical, layered architecture that enables the integration of various technologies to support smart city applications. The microverse is designed to be a dynamic, purpose-built ecosystem that streamlines task completion, enhances collaboration, and offers immersive professional settings. The paper presents a case study of a SPSS microverse prototype, which demonstrates the feasibility of the microverse in practical smart city applications. The prototype includes a network of surveillance cameras, drones, and sensors, and uses technologies such as digital twins and AI to enable real-time surveillance tasks. The prototype is tested with various configurations, including different bit rates and resolutions, and the results show that the microverse can achieve low latency and high throughput, meeting the requirements for most scenarios in real-world SPSS applications. The paper concludes that the microverse is a promising solution for smart cities, offering a task-oriented, edge-scale, pragmatic approach to integrating smart city technologies. Future work includes extending the microverse to incorporate more sophisticated algorithms applicable to RGB and thermal live feeds, as well as enhancing interoperability and compatibility with other standards. The microverse has the potential to significantly enhance the functionality of digital twin ecosystems and foster a more sophisticated, intelligent convergence of the virtual and physical worlds.The Microverse: A Task-Oriented Edge-Scale Metaverse This paper introduces the microverse, a task-oriented, edge-scale solution for smart cities, designed to address the challenges of integrating smart city technologies such as IoT, edge-fog-cloud computing, and AI. The microverse is a digital twin of an individual network slice, enabling on-site/near-site data processing, information fusion, and real-time decision-making within the edge-fog-cloud computing framework. Unlike all-encompassing metaverses, each microverse instance serves a specific task as a manageable digital twin of an individual network slice. The microverse concept is verified using smart public safety surveillance (SPSS) for smart communities as a case study, demonstrating its feasibility in practical smart city applications. The paper discusses the challenges of integrating the metaverse with IoT, including bandwidth and latency constraints, scalability, interoperability, security, and privacy. It also explores the enabling technologies of the metaverse, including digital twins, network slicing, and lightweight blockchain. The microverse framework is proposed as a hierarchical, layered architecture that enables the integration of various technologies to support smart city applications. The microverse is designed to be a dynamic, purpose-built ecosystem that streamlines task completion, enhances collaboration, and offers immersive professional settings. The paper presents a case study of a SPSS microverse prototype, which demonstrates the feasibility of the microverse in practical smart city applications. The prototype includes a network of surveillance cameras, drones, and sensors, and uses technologies such as digital twins and AI to enable real-time surveillance tasks. The prototype is tested with various configurations, including different bit rates and resolutions, and the results show that the microverse can achieve low latency and high throughput, meeting the requirements for most scenarios in real-world SPSS applications. The paper concludes that the microverse is a promising solution for smart cities, offering a task-oriented, edge-scale, pragmatic approach to integrating smart city technologies. Future work includes extending the microverse to incorporate more sophisticated algorithms applicable to RGB and thermal live feeds, as well as enhancing interoperability and compatibility with other standards. The microverse has the potential to significantly enhance the functionality of digital twin ecosystems and foster a more sophisticated, intelligent convergence of the virtual and physical worlds.