In the contemporary world of neoliberalism, efficiency is treated as the vehicle of political and economic health .State bureaucracy, but not corporate bureaucracy, is seen as inefficient, and privatization is seen as a magic cure for social ills. In Public Things: Democracy in Disrepair, Bonnie Honig asks whether democracy is possible in the absence of public services, spaces, and utilities. In other words, if neoliberalism leaves to democracy merely electoral majoritarianism and procedures of deliberation while divesting democratic states of their ownership of public things, what will the impact be? Following Tocqueville, who extolled the virtues of “pursuing in common the objects of common desires,” Honig focuses not on the demos but on the objects of democratic life. Democracy, as she points out, postulates public things—infrastructure, monuments, libraries—that citizens use, care for, repair, and are gathered up by. To be “gathered up” refers to the work of D. W. Winnicott, the object relations psychoanalyst who popularized the idea of “transitional objects”—the toys, teddy bears, or favorite blankets by way of which infants come to understand themselves as unified selves with an inside and an outside in relation to others. The wager of Public Things is that the work transitional objects do for infants is analogously performed for democratic citizens by public things, which press us into object relations with others and with ourselves. Public Things attends also to the historically racial character of public things: public lands taken from indigenous peoples, access to public goods restricted to white majorities. Drawing on Hannah Arendt, who saw how things fabricated by humans lend stability to the human world, Honig shows how Arendt and Winnicott—both theorists of livenesss—underline the material and psychological conditions necessary for object permanence and the reparative work needed for a more egalitarian democracy.

The pervasive application of Internet of Things (IoT) has been seen in many aspects in human daily life and industrial production. The concept of IoT originates from traditional machine-to-machine (M2M) communications which aimed at solving domain-specific and applicationspecific problems. Today, the rapid progress of communication technologies, the maturation of Internet infrastructures, the continuously reduced cost of sensors, and emergence of more open standards, have witnessed the approaching of the expected IoT era, which envisions full connectivity between the physical world and the digital world via the Internet protocol. The popularity of cloud computing technology has enhanced this IoT transform, benefiting from the superior computing capability and flexible data storage, let alone the security, reliability and scalability advantages. However, there are still a series of obstacles confronted by the industry in deployment of IoT services. First, due to the heterogeneity of hardware devices and application scenarios, the interoperability and compatibility between link-layer protocols, sub-systems and back-end services are significantly challenging. Second, the device management requires a uniform scheme to implement the commissioning, communication, authorization and identity management to guarantee security. Last, the heterogeneity of data format, speed and storage mechanism for different services pose a challenge to further data mining. This thesis aims to solve these aforementioned challenges by proposing a data-centric IoT framework based on public cloud platforms. It targets at providing a universal architecture to facilitate the deployment of IoT services in massive IoT and broadband IoT categories. The framework involves three representative communication protocols, namely WiFi, Thread and Lo-RaWAN, to enable support for local, personal, and wide area networks. A security assessment taxonomy for wireless communications in building automation networks is proposed as a tool to evaluate the security performance of adopted protocols, so as to mitigate potential network flaws and guarantee the security. Azure cloud platform is adopted in the framework to provide device management, data processing and storage, visualization, and intelligent services, thanks to the mature cloud infrastructure and the uniform device model and data model. We also exhibit the value of the study by applying the framework into the digitalization procedure of the green plant wall industry. Based on the framework, a remote monitoring and management system for green plant wall is developed as a showcase to validate the feasibility. Furthermore, three specialized visualization methods are proposed and a neuron network-based anomaly detection method is deployed in the project, showing the potential of the framework in terms of data analytics and intelligence.