The planning of metering network infrastructure based on the concept of the Internet of Things primarily involves the choice of available radio technology. Then, regardless of the type and availability of power sources, energy conservation should be one of the main optimization criteria. For this reason, LPWANs operating in unlicensed ISM bands appear to be a suitable solution in urban environments due to their sub 1 GHz propagation properties. High signal penetration and coverage make them applicable in urban areas with buildings and various obstacles. Therefore, this article presents solutions developed to support the planning process of implementing a LoRaWAN network infrastructure aimed at monitoring and collecting electricity meter data in smart cities. To this end, an algorithm has been proposed to support the selection of the number of LoRaWAN gateways and their deployment, as well as the selection of transmission parameters at the measurement nodes with a particular focus on geographic data from real maps.

Epidemics and pandemics dramatically affect mobility trends around the world, which we have witnessed recently and expect more of in the future. A global energy crisis is looming ahead on the horizon and will redefine the transportation and energy usage patterns, in particular in large cities and metropolitan areas. As the trend continues to expand, the need to efficiently monitor and manage smart city infrastructure, public transportation, service vehicles, and commercial fleets has become of higher importance. This, in turn, requires new methods for dissemination, collection, and processing of data from massive number of already deployed sensing devices. In order to transmit these data efficiently, it is necessary to optimize the connection structure in wireless networks. Emerging open access to real data from different types of networked and sensing devices should be leveraged. It enables construction of models based on frequently updated real data rather than synthetic models or test environments. Hence, the main objective of this article is to introduce the concept of network modeling based on publicly available geographic location data of heterogeneous nodes and to promote the use of real-life diverse open data sources as the basis of novel research related to urban sensor networks. The feasibility of designed modeling architecture is discussed and proved with numerous examples of modeled spatial and spatiotemporal graphs, which are essential in opportunistic routing-related studies using the methods which rely on graph theory. This approach has not been considered before in similar studies and in the literature.

Research into the topology control of Wireless Sensor Networks (WSNs) is geared towards modeling and analysis of methods that may be potentially harnessed to optimize the structure of connections. However, in practice, the ideas and concepts provided by researchers have actually been rarely used by network designers, while sensor systems that have already been deployed and are under continued development in urban environments frequently differ from the patterns and research models available. Moreover, easy access to diversified wireless technologies enabling new solutions to be empirically developed and popularized has also been conducive to strengthening this particular trend.

The optimization of network topology is crucial to achieve efficient data transmission in wireless sensor networks. Recently it has been proven that emerging open data sources can be used for modeling the structures of heterogeneous urban sensor networks. With this, leveraging real location data of various networked and sensing devices became feasible and essential. This approach enables the construction and analysis of more accurate representations based on frequently updated actual network infrastructure topology data, as opposed to using synthetic models or test environments. The presented modeling method serves as the basis for the designed architecture and implemented research environment. This paper introduces a set of algorithms which transform devices’ location data into graph-based wireless network connectivity models. Each algorithm is thoroughly discussed and evaluated. Moreover, static (momentary) and dynamic (time-spanning) network topologies are constructed in four large Polish cities based on publicly available data. Multidimensional simulation-based analysis is conducted to investigate the characteristics of the modeled structures. Directions for further research are suggested as well.

The development of network functionalities in the urban environment is accompanied by the emergence of new publicly available data sources. They are the basis of the introduced research architecture and environment which are used to investigate the new multicast algorithms proposed in this paper. These message-oriented algorithms are primarily intended to meet the needs of opportunistic routing in heterogeneous urban sensor networks. Although, due to their generalized and protocol-agnostic design, they can be of use in other network applications and research areas. Uncontrolled mobile relay devices are the key elements of the presented delay-tolerant multicast framework. Multicast structures are modeled in four Polish cities based on open data on the location of public transportation vehicles and elements of urban infrastructure. Over 16,000 graphs were built and analyzed. It has been shown that the use of uncontrolled mobile relay enables the construction of time-spanning time-changing multicast structures. Their features are determined by the topology of a given city area, the distribution of destination nodes, as well as the number and the routes of mobile relay nodes. The efficacy and efficiency of the algorithms depend on the radio range of the nodes, maximum time span of forwarded messages, and network structure knowledge availability.