Financing sustainable energy for all: pay-as-you-go vs. traditional solar finance approaches in Kenya

This paper focuses on finance for Solar Home Systems (SHSs) in Kenya and asks to what extent emerging new finance approaches are likely to address the shortcomings of past approaches. Drawing on the STEPS Pathways Approach we adopt a framing that understands finance within a broader socio-technical context as a necessary but not sufficient component of achieving alternative pathways to sustainable energy access. The paper contributes in four ways. Firstly, it presents a comprehensive overview of past and new emerging approaches to financing SHSs in Kenya and their relative strengths and weaknesses. Secondly, it represents one of the first attempts in the literature to analyse the potential of new, real time monitoring technologies and pay as you go finance models to overcome the barriers faced by conventional consumer finance models for off-grid renewable energy technologies (RETs). Thirdly, by applying for the first time we are aware of a socio-technical approach, via the application of Strategic Niche Management (SNM) theory, to analyse the finance of RETs in developing countries, the analysis considers finance in the context of the social practices poor people seek to fulfil via access to the energy services that off-grid RETs provide, and the ways in which people previously paid for these services (e.g. via kerosene for lighting). This also situates the analysis within the understanding of SHSs as a niche that has to compete with the established regime of energy service provision and its attendant social and political institutional support. The paper therefore also contributes to the small but expanding body of literature that seeks to operationalise socio-technical transitions thinking and SNM within a developing country context

Standards as a driving force that influences emerging technological trajectories in the converging world of the Internet and things: An investigation of the M2M/IoT patent network

While standards are said to create windows of opportunity in facilitation of technological convergence, it is not clear how they affect technological trajectories and strategic choices of firms in the face of convergence and in the process of catch-up. There is little research on the relationship between standards and technological trajectories, particularly in the age of convergence. This paper investigates how standards shape the emerging M2M/IoT technological trajectory and influence convergence in terms of technological importance and diversity. We, firstly, found that standards are a driving force of technological convergence. The second finding is that 3GPP standards assume a crucial role in setting the boundary conditions of the M2M/IoT technological systems. Third, we identified strategic groups and strategic patents that centered around the M2M/IoT trajectory. Forth, standards serve as an important factor in the process of creating a new path for catch-up firms (e.g. Huawei). These findings make contributions to innovation and standards studies by empirically examining the relationship between technological trajectories and standards. Furthermore, they clearly cast light on ongoing cooperation and competition along the M2M/IoT trajectory, and offer practical implications for catch-up strategies

The design and implementation of a smart-parking system for Helsinki Area

The strain on the parking infrastructure for the general public has significantly grown as a result of the ever rising number of vehicles geared by the rapid population growth in urban areas. Consequently, finding a vacant parking space has become quite a challenging task, especially at peak hours. Drivers have to cycle back and forth a number of times before they finally find where to park. This leads to increased fuel consumption, air pollution, and increased likelihood of causing accidents, to mention but a few. Paying for the parking is not straight forward either, as the ticket machines, on top of being located at a distance, in many times, they have several payment methods drivers must prepare for. A system therefore, that would allow drivers to check for the vacant parking places before driving to a busy city, takes care of the parking fee for exact time they have used, manages electronic parking permit, is the right direction towards toppling these difficulties. The main objective of this project was to design and implement a system that would provide parking occupancy estimation, parking fee payment method, parking permit management and parking analytics for the city authorities. The project had three phases. The first and the second phases used qualitative approaches to validate our hypotheses about parking shortcoming in Helsinki area and the recruitment of participants to the pilot of the project, respectively. The third phase involved the design, implementation and installation of the system. The other objective was to study the challenges a smart parking system would face at different stages of its life cycle. The objectives of the project were achieved and the considered assumption about the challenges associated with parking in a busy city were validated. A smart parking system will allow drivers to check for available parking spaces beforehand, they are able to pay for the parking fee, they can get electronic parking permits, and the city authority can get parking analytics for the city plannin

Optimizing performance and energy efficiency of group communication and internet of things in cognitive radio networks

Data traffic in the wireless networks has grown at an unprecedented rate. While traditional wireless networks follow fixed spectrum assignment, spectrum scarcity problem becomes a major challenge in the next generations of wireless networks. Cognitive radio is a promising candidate technology that can mitigate this critical challenge by allowing dynamic spectrum access and increasing the spectrum utilization. As users and data traffic demands increases, more efficient communication methods to support communication in general, and group communication in particular, are needed. On the other hand, limited battery for the wireless network device in general makes it a bottleneck for enhancing the performance of wireless networks. In this thesis, the problem of optimizing the performance of group communication in CRNs is studied. Moreover, energy efficient and wireless-powered group communication in CRNs are considered. Additionally, a cognitive mobile base station and a cognitive UAV are proposed for the purpose of optimizing energy transfer and data dissemination, respectively. First, a multi-objective optimization for many-to-many communication in CRNs is considered. Given a many-to-many communication request, the goal is to support message routing from each user in the many-to-many group to each other. The objectives are minimizing the delay and the number of used links and maximizing data rate. The network is modeled using a multi-layer hyper graph, and the secondary users\u27 transmission is scheduled after establishing the conflict graph. Due to the difficulty of solving the problem optimally, a modified version of an Ant Colony meta-heuristic algorithm is employed to solve the problem. Additionally, energy efficient multicast communication in CRNs is introduced while considering directional and omnidirectional antennas. The multicast service is supported such that the total energy consumption of data transmission and channel switching is minimized. The optimization problem is formulated as a Mixed Integer Linear Program (MILP), and a heuristic algorithm is proposed to solve the problem in polynomial time. Second, wireless-powered machine-to-machine multicast communication in cellular networks is studied. To incentivize Internet of Things (IoT) devices to participate in forwarding the multicast messages, each IoT device participates in messages forwarding receives Radio Frequency (RF) energy form Energy Transmitters (ET) not less than the amount of energy used for messages forwarding. The objective is to minimize total transferred energy by the ETs. The problem is formulated mathematically as a Mixed Integer Nonlinear Program (MINLP), and a Generalized Bender Decomposition with Successive Convex Programming (GBD-SCP) algorithm is introduced to get an approximate solution since there is no efficient way in general to solve the problem optimally. Moreover, another algorithm, Constraints Decomposition with SCP and Binary Variable Relaxation (CDR), is proposed to get an approximate solution in a more efficient way. On the other hand, a cognitive mobile station base is proposed to transfer data and energy to a group of IoT devices underlying a primary network. Total energy consumed by the cognitive base station in its mobility, data transmission and energy transfer is minimized. Moreover, the cognitive base station adjusts its location and transmission power and transmission schedule such that data and energy demands are supported within a certain tolerable time and the primary users are protected from harmful interference. Finally, we consider a cognitive Unmanned Aerial Vehicle (UAV) to disseminate data to IoT devices. The UAV senses the spectrum and finds an idle channel, then it predicts when the corresponding primary user of the selected channel becomes active based on the elapsed time of the off period. Accordingly, it starts its transmission at the beginning of the next frame right after finding the channel is idle. Moreover, it decides the number of the consecutive transmission slots that it will use such that the number of interfering slots to the corresponding primary user does not exceed a certain threshold. A mathematical problem is formulated to maximize the minimum number of bits received by the IoT devices. A successive convex programming-based algorithm is used to get a solution for the problem in an efficiency way. It is shown that the used algorithm converges to a Kuhn Tucker point