In a nearby future 5G technologies will connect the world from the largest megacities to the smallest internet of things in an always online fashion. Such a connected hierarchy must combine the smart cities, the smart homes, and the internet of things into one large coherent infrastructure. This paper suggest a four layer model which join and interfaces these elements by deploying technologies such as 5G, internet of things, cloud of things, and distributed artificial intelligence. Many advantages and service possibilities are offered by this new infrastructure such as interconnected internet of things, smart homes with artificial intelligence, and a platform for new combined smart home and smart city services based on big-data.

Cognitive radio is the emerging technology which provide the innovative approach to improve the spectrum utilization and alleviate the spectrum scarcity. Evaluation of the spectrum occupancy is the step toward the future deployment of cognitive radio. Worldwide several spectrum occupancy measurement campaigns have been performed at different location in context of cognitive radio. We reviewed past measurement campaigns performed by different research groups and analysis of empirical results. We further provide a spectrum occupancy measurement framework for the proposed spectrum measurement in India.

The world is entering a new era, where Internet-of-Things (IoT), smart homes, and smart cities will play an important role in meeting the so-called big challenges. In the near future, it is foreseen that the majority of the world’s population will live their lives in smart homes and in smart cities. To deal with these challenges, to support a sustainable urban development, and to improve the quality of life for citizens, a multi-disciplinary approach is needed. It seems evident, however, that a new, advanced Information and Communications Technology ICT infrastructure is a key feature to realize the “smart” vision. This paper proposes a specific solution in the form of a hierarchical layered ICT based infrastructure that handles ICT issues related to the “big challenges” and seamlessly integrates IoT, smart homes, and smart city structures into one coherent unit. To exemplify benefits of this infrastructure, a complex IoT system has been deployed, simulated and elaborated. This simulation deals with wastewater energy harvesting from smart buildings located in a smart city context. From the simulations, it has been found that the proposed infrastructure is able to harvest between 50% and 75% of the wastewater energy in a smart residential building. By letting the smart city infrastructure coordinate and control the harvest time and duration, it is possible to achieve considerable energy savings in the smart homes, and it is possible to reduce the peak-load for district heating plants.

The remote monitoring of patients using the internet of things (IoT) is essential for ensuring continuous observation, improving healthcare, and decreasing the associated costs (i.e., reducing hospital admissions and emergency visits). There has been much emphasis on developing methods and approaches for remote patient monitoring using IoT. Most existing frameworks cover parts or sub-parts of the overall system but fail to provide a detailed and well-integrated model that covers different layers. The leverage of remote monitoring tools and their coupling with health services requires an architecture that handles data flow and enables significant interventions. This paper proposes a cloud-based patient monitoring model that enables IoT-generated data collection, storage, processing, and visualization. The system has three main parts: sensing (IoT-enabled data collection), network (processing functions and storage), and application (interface for health workers and caretakers). In order to handle the large IoT data, the sensing module employs filtering and variable sampling. This pre-processing helps reduce the data received from IoT devices and enables the observation of four times more patients compared to not using edge processing. We also discuss the flow of data and processing, thus enabling the deployment of data visualization services and intelligent applications.