# CrowdPower: A Novel Crowdsensing-as-a-Service Platform for Real-Time Incident Reporting
### Research Scope  
The main challenges to realizing both the client and server side of the MSaaS platform are as follows. The first challenge is to capture data using different frequencies (e.g., once, time-based, event-based) and spanning different contribution scales (i.e., individual, group, and community). The next challenge is managing mobile users with varying devices' capabilities and recruiting reliable users for a sensing campaign with different sensing paradigms (i.e., both opportunistic and participatory). The next challenge is to automatically process and determine the quality of the raw sensory data received, optimize processing efforts, and transform the data into useful reports. The other challenge is the requirement to broker the communication between data collectors and data consumers in a structured manner using standard protocols. To address these challenges, we designed and implemented CrowdPower, a novel end-to-end MSaaS platform. CrowdPower allows tapping into the sensing capabilities of existing smartphones to collect the needed intelligence in an on-demand and resource-efficient manner. CrowdPower acts as an intermediary between data consumers (i.e., smart city applications) and data collectors (i.e., sensor-enabled mobile devices) by matching sensing requests in real-time with the most suitable sources and offering information management and data brokerage capabilities. The platform enables the management of various mobile sensing data efficiently and supports different sensing paradigms (i.e., both opportunistic and participatory sensing). To ensure the modularity and extensibility of the system, the platform design leverages SOA (Service Oriented Architecture) concepts to offer its functionalities as RESTful services. Furthermore, it includes AI-based capabilities for evaluating data quality and the automatic generation of incidents' intelligence reports from raw sensory data. CrowdPower also includes a sensing mobile application that enables data collectors and data consumers to participate in sensing activities. Finally, an administration Web portal is also devised to enable the management of sensing activities and obtain visualization of sensing sessions and incident reports. As depicted in Figure 1, our use case encompasses a set of data consumers (interested in crowd-sensed data), data collectors (participants collecting the requesting data using their phone), and the CrowdPower MSaaS platform acting as the broker between data consumers and data collectors. Data collectors and data consumers are registered on the platform using the CrowdPower mobile app. The platform collects status information (i.e., updated location and sensors' availability) from data collectors' mobile applications to keep track of all available data types and the associated quality levels offered to data consumers. To illustrate CrowdPower, consider the example of a data consumer needing data to be collected about a car accident in a certain location in the city. As a result, the data consumer sends a sensing request to CrowdPower, matching the requirements and the available data collectors' status information to find the appropriate set of collectors who can respond to the request. When a data consumer sends a request to the broker, the request specifies the type and location of the event of interest, along with the minimum quality level required for the task, the maximum budget allocated, as well as the maximum time window required for the task (e.g., car accident at location, min. quality level of 8, max. budget of USD 10, and max. time window of 5 min). Once the selection of collectors (participant selection) is complete, the request is transmitted to the chosen data collector's mobile app. The participants who accept the received sensing task would complete the sensing activity either manually (e.g., taking a picture or video of an incident) or automatically (sensory data automatically collected by the app.) and transmit the resulting sensed data to the platform.