Crowd Sensing as a Solution to Campus Overcrowding

The issue of traffic congestion around large campuses is becoming chronic and it needs to be immediately addressed. In a nutshell, the issue is facing many congested area and which calls for a long lasting solution to be sought. Several other methods that are being used to curb this problem have proved to be inefficient and ineffective. The same issue is facing this campus university and in a bid to find its solution, I would recommend to the campus manager to embrace the mobile crowdsensing technology because it seems to be the solution to this problem.

Firstly, it would be important to appreciate how the technology was developed and how it works. Mobile Crowdsensing is a technology where a large crowd of people with mobile devices such as smartphones, tablets computers among others that have the capability to compute sense and share data with the other devices around that area. Despite the fact that this is a growing technology, it has proved to be very beneficial if utilized correctly. This syatem is similar to a geographic information system only that it makes use of phones that sense data and sends it to the nearby servers. Apart from sending data to the servers, the data can aslso be sent to the nearby devices which allows distribution of valuable data to various consumers as stated by Liu, Shen, and Zhang, (2016). Mobile crowd sensing has become an immediate source of crowdsourced geographical information dispensed to the numerous mobile devices carried by the people globally that support their movement. The data is clarified, amassed, analyzed and processed at the servers and notifications with relevant information are then sent to the mobile users to support their movement. The mobile device owners act as the sources of this data. These people also make use of the same data after it undergoes synthesis in the servers.

There are very many demonstration applications that have been developed to illustrate how mobile crowd sensing can be used in different city settings and provide an acumen of how similar applications can improve the kinesis within these towns. Despite the fact that the technology is in its initial stages of development, it looks promising since it has a variety of applications that would have otherwise made the world lag behind.

The mobile devices that can be used have environmental sensors, virtual sensors and social sensors that act as the source of the mobile sensed data. Physical sensors are the sensors mounted on these devices. They range from GPS, microphone, proximity sensors, compass, gyroscope, accelerometer, ambient light sensor, and cameras to other sophisticated sensors like the humidity and temperature sensors that are mounted on more advanced mobile devices. It is the data that is collected by these sensors that is sent to the servers and becomes useful when analyzed.

Drivers, motorists and pedestrians have been used in many cases as the sources of such data. These people have mobile devices that collect traffic data in various places that they travel to. And because they do not stay at one point, their mobile devices send data of different places to the servers. This data is then analyzed and synthesized. It’s then made available to them and the other citizens who can then make use of it to plan their travel.

Types of Mobile Crowdsensing

There are a few traffic events that can be reported. They include: the travel epochs, traffic halts, parking places, congestion localities, slackened traffic, etc. the state of the extensive infrastructure that can be reported include rough roads, dicey road surface, dented roads/potholes, etc. this falls under infrastructural mobile crowdsensing. The changing traffic events that can be reported include sudden increase and decrease in speed, lateral slipping change of direction and traffic lanes, accidents, etc. this information is then sent to the drivers in the affected routes and an alternative route is proposed to avoid the issue that has been noticed and therefore reported. This leads to safety on the roads which is then translated to efficiency in the transport system.

Opportunistic crowdsensing is where data is sent from the mobile users automatically, and after its analysis, it can easily be used by the consumers. This is one of the most important techniques that can be applied around the campus since all such information can be relayed to the students who possess many strong devices that can collect such information. The information will then enable them to know the routes to follow at a particular time, and this can increase the security around the area, and traffic congestion will reduce. No one wants to be caught in traffic thus alternative routes will start to be used. Another type of crowdsensing is the participatory crowdsensing. This involves the users of the different routes sending data regarding their positions to the servers, and this data is then availed to the other users

Environmental crowdsensing is also another type of mobile crowdsensing where data about the environment is collected using the mobile sensors of the mobile device users. This data is then made available to the rest of the users around the area who have access to the data server. This information may include environmental pollution, the temperatures, humidity, and cloud cover, etc. if such a system was introduced in the campus, the students could then know when to travel, when to wear what type of gear, attire etc. for example, if data shows that there will be a thick cloud cover that can result to some rainfall then the students can wear heavy clothes and carry umbrellas.

Social crowdsensing shows social activities taking place around a particular area. Such activities include sporting activities etc. If this piece of technology can be employed on the campus, then it can be easy to know the itineraries that people are taking maybe when skating when going to various recreational activities, etc. students can then use the data to find out where to be at what time and the kind of activities taking place there.

Potential Benefits of Mobile Crowdsensing

Mobile Crowdsensing has various advantages. Firstly, the data that is obtained has multiple uses such as predicting the weather, knowing the routes to follow and knowing the social activities taking place at a certain place within a particular period. This data can be very useful to the students in campus if it is made available to them. It can help them know the routes to follow, the type of whether they expect and the social activities taking place in a certain area around the campus. Also, it boosts development in technology in that many people are conducting research to produce a more reliable analogous system. Most of the students like to have reliable and efficient systems. The students in the campus will therefore be attracted to doing more research and identify the means through which this system can be improved thus improving their knowledge.

A major benefit of the technology is that it can help in reducing traffic congestion around populated areas which is the biggest problem that is facing urban centers. The system has proved to be more reliable than everyone could imagine. Since there is a problem of traffic congestion in the campus, introduction of this system can be so helpful since the data can be collected using the student’s mobile devices and when it is analyzed, it becomes useful to them

Challenges of Mobile Crowdsensing

There are some challenges that come about with mobile crowdsensing. According to Ganti, Ye and Lei, (2011), the quality of the data sent can impose a problem in that some users are not honest and can send malicious data to the system. Students in campus may want to mislead others by either hacking into the system or even sending malicious data. This can be overcome by introducing opportunistic crowdsensing where it is the sensors that determine the data to be transmitted and not the user. User anonymity is also another challenge where sensitive data about the users can be sent. Data such as GPS locations can be used for other purposes other than those of MCS. Safety of the students must be guaranteed at all cost. The problem of user anonymity can be solved through anonymizing data, secure multiparty computation, and data perturbation.

Conclusion

As evidenced from the above discussion, the problem of traffic congestion in and around the campus can be addressed by embracing the mobile crowdsensing technology. This is because the technology can easily be applied in the campus since the students have mobile devices that can collect and relay traffic, environmental and social data to a server, this data can then be synthesized and sent back to the students as important information that shows the nature of traffic, weather and social activities. This would in return help them to choose the best routes to follow thus minimizing congestion.