# CrowdPower: A Novel Crowdsensing-as-a-Service Platform for Real-Time Incident Reporting
## 2 Related Work and Literature Review  
Smart cities are continuously innovating to use information and communication technologies to solve major challenges of urban life, such as traffic congestion, environmental pollution, waste management, and regulation of health requirements. These requirements of smart cities are enabled using service-oriented architecture, which promotes cost-effective, seamless, and efficient communication between a network of sensors (including WSNs) and a cloud computing platform. With sensors being widely deployed in smart cities and the possibility of accessing everything-as-a-service over the Internet, this has enabled the scalability and availability of the various urban services [18; 19]. Yet, the challenge remains: deploying and maintaining these dedicated sensing platforms and sensory networks are expensive. Recently, with the advent of powerful smartphones that have embedded sensors, the possibility of using these mobile smartphones as sensing platforms caught the interest of researchers, leading to the concept of mobile phone sensing [20]. Table 1, presents a comparison between the traditional sensing paradigm (i.e., WSNs) and mobile sensing. The main objective of the literature review is to show how CrowdPower compares with the existing tools and also to highlight the research gaps in the literature. However, this article is not considered a systematic literature review. In finding the related work, we minimized the bias by searching for articles using widely used search libraries such as Scopus, and we used keywords relevant to our work, such as \"sensing\", \"crowdsensing\", and \"platform\", among others. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **Mobile Phone Sensing** & **Traditional Sensing (WSNs)** \\ \hline
**Processing Capability** & High & Limited \\
**Storage Capability** & High & Limited \\
**Power Supply** & **R**echargeable & Battery-powered, needs maintenance \\
**Computing** & **Distributed, each node is intelligent** & Relies on a centralized external server \\
**Data Support** & **Supports raw or processed data** & Can only support raw data \\
**Security** & **Standard smartphone security protocols such as** & Limited options for ensuring security \\
**Ownership** & **All mobile users** & Typically, organizations that deploy WSNs \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of WSN and mobile phone sensing. Mobile phone sensing is ideal for sensing applications since it uses the widely available, self-maintained, comparatively secure, cost-effective, and resource-rich platform of an already existing infrastructure of mobile phones [21, 22]. Moreover, the development of mobile crowdsensing applications is scalable and easily adaptable when designed with SOA concepts [23, 24], since it allows the decoupling of sensing applications from the sensing hardware. Such crowdsensing platforms offer seamless participant recruitment, data collection, data processing, and data dissemination services. As described earlier, Crowd-Power offers SOA along with extensive RESTful Web services to expose its functionality as services. Table 2 presents a comparison of the crowdsensing platforms that use mobile sensing and would help the reader to identify and compare our contributions in comparison to existing solutions. A middleware that automates the process of users finding and joining online social network services and collecting contextual data is [25]. It combines user activities on such services by sensing the physical environment using mobile devices while maintaining privacy. Hence, applications easily capture both user context and sensed data. The key features are that users can build an application on SenSocial for social media monitoring and define their triggers for sensing. The framework has a close coupling of social networks and mobile sensing data streams which can be filtered. The Publish-Subscribe interaction paradigm is used where the middleware is the publisher, and the applications are the subscriber.