Internet of Things (IoT) provides large-scale interoperable service delegations for heterogeneous users through pervasive access. The interconnection of different devices and services in an on-demand and pervasive manner provides seamless responses for different applications. However, a few interconnected devices are stuck into a resource-constraint problem due to limited access and unavailability. This article proposes an interoperable access framework (IAF) for pervasive application services (PAS) for providing robust end-user solutions. The proposed framework balances the accessibility and semantics and its responses for providing seamless interoperability support. In this framework, transfer learning for different limited and free-flow service accessibility is used. The teaching is recurrent for identifying the unavailability of the resources. The process of serving the requests is achieved through interoperable replacement services. It reduces the impact of resource-constraint in the IoT platform, wherein the semantics between unavailability and accessibility is analyzed flawlessly. The proposed framework's performance is verified using the metrics service delay, responses, unavailability, resource utilization, and successful access.

物联网（IoT）通过普遍访问为异构用户提供了大规模的可互操作服务委托。按需和普遍的方式互连不同的设备和服务为不同的应用程序提供了无缝的响应。但是，由于访问受限和不可用，一些互连的设备陷入了资源受限的问题。本文提出了一种用于普适应用程序服务（PAS）的互操作访问框架（IAF），以提供可靠的最终用户解决方案。所提出的框架在可访问性和语义及其响应之间取得了平衡，以提供无缝的互操作性支持。在此框架中，使用了针对不同的受限和自由流服务可访问性的转移学习。该教学是反复进行的，以识别资源的不可用。服务请求的过程是通过可互操作的替换服务实现的。它减少了资源约束在物联网平台中的影响，从而完美地分析了可用性和可访问性之间的语义。使用度量标准服务延迟，响应，不可用性，资源利用和成功访问来验证所提出框架的性能。