# A Serious Gaming Approach for Crowdsensing in Urban Water Infrastructure with Blockchain Support
## 8 Discussion  
The simulation environment provides an evaluation of platform-centric and user-centric approaches to MCS. The task allocation and incentive mechanism represent two different problems that can be solved by either approach, while there are some specific aspects given by the geolocation component.  
The player locations and distribution of tasks within a geographic area represent a key aspect in selecting the most suitable method for designing the incentive mechanism. In this sense, the VRP is a highly studied, industry-proven method that was adapted for this scenario and represents a platform-centric approach, while the VCG provides a user-centric reward mechanism based on player reputation in a reverse-auction model, where the actual  
Figure 16: Write average latency (**a**) single write; (**b**) batch write.  
Figure 15: Read average latency (**a**) single read; (**b**) batch read.  
sensing cost is reported by each player, instead of relying on a central dispatch system. The proposed solution offers great opportunities for further research by assessing both platform and user-oriented approaches.  
Geolocation is a sensitive subject with regards to user privacy, which makes VCG a viable alternative for the reward-driven routing problem as well, demonstrated through the experimental results. While the location must be provided for georeferencing and map loading, the continuous tracking of user location not only can be resource-intensive, but may be prohibited by privacy laws. Therefore, an initial allocation of tasks is handled by the VRP model, while the dynamic reward mechanism is more accurately defined by the VCG model, where the actual sensing cost, i.e., distance traveled, is reported by each player.  
A potential issue with crowdsensing is given by duplicate reporting, which can be addressed by a second reward factor based on the density of the reports within a geographic area in terms of physical location, category and timestamp. Moreover, by assigning lower rewards for clustered reports and higher rewards for outlier reports, the coverage of the proposed MCS solution can be improved.  
Ambiguous reporting is another aspect that can be solved by integrating multiple validation schemes, i.e., using more accurate categories for reported issues and combined sensor data (e.g., camera, microphone) along with text-based reports. A more accurate rating system can further improve the level of interaction between the participants and encourage both truthful and accurate reporting.  
While both platform-centric and user-centric models aim at increasing coverage, the integration in a real-time MCS platform based on the serious game implementation defined in this paper represents a challenge to be discussed in future research. The SG platform design is of primary importance when considering the actual involvement of citizens in solving water-related problems, with a game-driven mobile interface that is both practical and entertaining for the users. An additional aspect is increasing the environmental awareness of users, as well as an educational function.  
The different stakeholders are assigned different roles, while the incentive mechanism is based on reputation and level of interaction with the real-world through gamified scenarios. The interactions are shaped by the incentive mechanisms and in-game economy for increased platform utility, i.e., optimal sensing capabilities.  
The trust-based mechanism is supported by the Hyperledger Fabric architecture, which provides a scalable blockchain solution for audit-enhanced storage layer, with peer nodes represented by major stakeholders in water utility networks. The global implications for MCS, i.e., increasing the level of participation, can be found in multiple studies presented in Section 2, while an additional improvement in terms of overall platform utility is given by the reduced energy requirements for consensus when compared to other blockchains.