Crowdsourcing in Mobile- A Three Stage Context Based Process

Ahmad Hassan Afridi Center of Excellence in IT

Institute of Management Sciences, Peshawar Pakistan

Abstract— Crowdsourcing is a new paradigm that has influenced the businesses, emergency management, collaboration and online interaction. The term crowdsource means tapping the power of crowd. Research in crowd sourcing involves issues such as quality of data, incentives, working modal and contracts. This research deals with the issues of uncertainty and quality of social mobile computing systems. It suggests the relationship between context and crowdsourcing activity. This understanding can enhance the future and existing applications in a way that it can optimize systems response, adapt the components and decrease the uncertainty.

Keywords-Crowdsourcing; Mobile Context Aware Systems

I. INTRODUCTION Crowdsourcing is known as tapping the power of crowd.

Crowdsourcing is promising area for research and development. The theme of the paper is to evaluate the mobile crowdsourcing systems, relationship of context awareness to the crowdsourcing triggers and a system engineering approach to it. It has brought the basic change in to the problem solving mechanism and new contract between users and servers. It has changed the use of mobile devices and further added dimensions such as patterns in mobility, activities and processes. Further the advancement and usage of technologies, user interface and social networking modals.

Crowdsourcing has brought change in the social computing landscape. Applications developed have impacted healthcare, labor economics, engineering and services.

II. RELATED WORK Our scope of study is related to the crowdsourcing carried out in on mobile platforms. Several projects have been done in the area of mobile crowdsourcing. Smart phones as sensors: The project disuses a method for developing a rapidly crowd sourcing applications [1]. The framework provides facility to write script, which users can write accordingly to its choice and requirements. It also discusses important steps in the engineering of crowd sourcing applications. Stress outsourced: The paper presents the crowd sourcing of therapeutic massages to relive the stress [2] . It presents the prototype of a system; a next generation of hardware interface for social interaction. A paradigm of hepatic social network

has been discovered, a trend in the mobility and scalability of tangibles and hepatic network. Crowd sourcing is influenced is four dimensions for impersonal crowd for problem solving, impersonal, personal and affective communication. Human computation: A survey and taxonomy: This research gives an over view of human computation tasks and taxonomy of crowd sourcing systems [3]. According to the taxonomy there are several dimensions of social networking systems. The paper describes the latest development in crowd sourcing and influence of social computing on the collaboration. The paper presents taxonomy of crowd sourcing systems, explaining the motivation to be part of crowd sourcing activities, what kind of contracts the worker, requester and computer enters. Fear and the city- Role of Mobile: The central theme of this research is safety in urban use contexts [4] . It presents with a prototype “comfort zones”. Females are subject to harassment and threats. The micro blogging effects in safety in security in urban mobility. Statistics show that during different phases of mobility, they showed signs of fear. Users enter their feeling in the system by updating their mental state. The states are recorded and presented in map form. The comfort and hostility zones are identified and can be put to various studies. Txteagle: A crowdsourcing platform to earn. This is done by translation, transcription and training speech recognition systems [5]. Application developed for Texas border surveillance, testing and marketing research, non-emergency neighborhood issues community activism, real time traffic jam updater covers major domains covered by mobile crowdsourcing and covers Reporting and journalism, Personal health and documentation, advertising, knowledge and emergency management [6].

III. CONTEXT AWARENESS & MOBILE CROWDSOURCING Context aware computing is a paradigm that involves the environmental awareness of the system and the system responds to the relative changes in the system. Context aware computing has been applied to many domains such as healthcare, engineering, manufacturing, homes and offices [7]. A typical context aware system is composed of several common layers such as sensors, aggregation layer, inference engine, knowledge base and application layer. Context aware systems have been deployed over a number of system including mobile and PDA devices. Some common examples of context aware system Context aware computing has been

2011 Ninth IEEE International Conference on Dependable, Autonomic and Secure Computing

978-0-7695-4612-4/11 $26.00 © 2011 IEEE

DOI 10.1109/DASC.2011.60

243

2011 Ninth IEEE International Conference on Dependable, Autonomic and Secure Computing

978-0-7695-4612-4/11 $26.00 © 2011 IEEE

DOI 10.1109/DASC.2011.60

243

2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing

978-0-7695-4612-4/11 $26.00 © 2011 IEEE

DOI 10.1109/DASC.2011.60

243

2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing

978-0-7695-4612-4/11 $26.00 © 2011 IEEE

DOI 10.1109/DASC.2011.60

242

worked for fault tolerance and dependability , as it’s an important factor for domains such as healthcare [8] . The context during the mobility changes dynamically and rapidly. Mobility offers challenges not only to the system but to the user as well. The overall context of a system is gauged into various categories of context. It depends upon the maturity dimensions of the system and now social aspect of the systems is gaining attention [9] [10] .

Our thesis revolves the idea that context of the mobile has an impact and a cause in the crowdsourcing forms that particular system. We assume that the system is mobile computing device and the user context is taken into account. The context of the user during the mobility is disturbed, compromised or abnormal for a prolong period of time. This imbalance is cause of the user to crowdsource the problem to other systems. Consider an emergency situation where a user needs help and he want to know the current location of the area of some information regarding nearby area. The users computing context is disturbed due to the non – availability signal. Also the user life is in danger and user context is not in equilibrium state. These contextual variables are result into the crowd sourcing of information from the user to the other peer mobile devices using ad-hoc network such as Bluetooth. The scenario is described in the figure 1.

Figure 1: Crowdsourcing in Mobile Devices

Similarly the context of the system changes when the computing or user context (ability/ disability) impacts on the understanding of the disaster hit area or emergency zone. For this reason the translation services are crowd sourced to other systems either mobile or fixed terminal computer systems. Context is dynamic in nature, it’s observed that

• Context is divided into two main types, internal context and external context

• There is interconnectivity between internal context and external context

• Internal and external context influence the crowdsourcing activity

• As the acceptable level of internal or external level of crowdsourcing is achieved, it effects in a pause stopping of crowdsourcing.

Figure 2: Relationship between External, Internal Context and Crowdsourcing

Internal context variables include Emotional state, ability, emergency and capability (physical), Abilities and Disabilities (tangible and intangible). External factors include Environmental factors such as Disaster/ Emergency, Temperature/ weather, People, groups, aura, place and location. Table-1 describes the cause of most of the crowdsourcing operations in literature. The causes are internal and external both and it has a profound impact on the overall system. Figure-3 explains the cause and effect relationship of contextual states and crowdsourcing. The system is in a loop operation and user keeps on crowdsourcing until the internal or external context factors are not in a favorable condition. The interdependency is explained by the triangle. The binding element between these three factors is the relationship, the contract among these three factors. For example the if there is a crowdsourcing activity for location information during emergency, there will be an urgency by the affected person whose internal context is anxious and unstable. This unstable context factor has been caused due to the emergency i.e. earthquake or fire in the area which shows an abnormal activity in the external context.

244244244243

Table -1: The Context Factors and Cowrdsourcing

Project Context Factors CrowdsourcingDomain

[4] External Context Place

Emergency and Security

[11][12] Internal Context Ability/Disability

Translation

[13] Internal Context Computing

Tagging

[11] Internal Context Translation

Translation

[2] Internal Context Motivation

Emotions

[6] External Context City and Environment

Community Activism

IV. 3 STAGE PROCESS

The Interdependency and benefit to the user most of the time too consumer of information and producer establish that contextual knowledge is contextual states can play a role in the optimization and enhancement of the system. These states are interdependent and if sensed and modeled can contribute to the crowdsourcing operations. For example if the mobile device is aware of the human health condition with an area where there is no doctor of hospital nearby, the crowdsourcing software can broadcast for nearest hospital or specialist doctor information in nearest location. If a person is shopping mall , he/she can set he profile for a specific shopping item , based upon the queries and responses can be evaluated for the best price or shop with more variety . This process can be summarized in these steps.

• The contextual state of client triggers the crowd

sourcing • Enters the contract which ensures mutual benefits ,at

least the user • Other people due to their contextual state are helpful

to clients

V. ENGINEERING OF MOBILE CROWDSOURCING SYSTEMS Engineering mobile crowdsourcing systems can be enhanced. Projects are directed towards the making adventurous trips, family life and mobile work a social activity can greatly benefit from using the context awareness.

• Cowrdsourcing system effectiveness of social

mobile systems • Adaptability and optimization of crowdsourcing

application with context awareness

• Dealing Uncertainty in Mobile Computing Devices.

Figure 3: Cause and Effect –Crowdsourcing and Context

VI. CONCLUSION AND FUTURE RESEARCH DIRECTION

We proposed a technique to evaluate the crowdsourcing system and its linkage with the context awareness. As industry is moving towards more social awareness and such systems are being integrated into the daily life style, engineering of such system will require evaluation and tracing of certain factors that cause the systems to act in a specific manner. Further such engineering techniques can be more streamlined for specific domain such as healthcare, assisted living technologies and social systems.

REFERENCES

[1] T. Kaler et al., “Code in the air: simplifying sensing on smartphones,” in Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, 2010, pp. 407-408.

[2] K. Chung, C. Chiu, X. Xiao, and P.-Y. (Peggy) Chi, “Stress outsourced: a haptic social network via crowdsourcing,” in Proceedings of the 27th international conference extended abstracts on Human factors in computing systems, 2009, pp. 2439-2448.

[3] A. J. Quinn and B. B. Bederson, “Human computation: a survey and taxonomy of a growing field,” in Proceedings of the 2011 annual conference on Human factors in computing systems, 2011, pp. 1403-1412.

[4] J. Blom, D. Viswanathan, M. Spasojevic, J. Go, K. Acharya, and R. Ahonius, “Fear and the city: role of mobile services in harnessing safety and security in urban use contexts,” in Proceedings of the

245245245244

28th international conference on Human factors in computing systems, 2010, pp. 1841-1850.

[5] N. Eagle, “txteagle: Mobile Crowdsourcing,” in Internationalization, Design and Global Development, vol. 5623, N. Aykin, Ed. Springer Berlin / Heidelberg, 2009, pp. 447-456.

[6] “List of crowdsourcing projects.” [Online]. Available: http://en.wikipedia.org/wiki/List_of_crowdsourcing_projects. [Accessed: 22-Aug-2011].

[7] A. H. Afridi and S. Gul, “Method Assisted Requirements Elicitation for Context Aware Computing for the Field Force,” in Proceedings of the International MultiConference of Engineers and Computer Scientists, 2008, vol. I.

[8] A. H. Afridi and M. Ali, “Fault Tolerent Context Aware Mobile Computing,” in Proceedings of the 2009 International Conference on Future Computer and Communication, 2009, pp. 617-621.

[9] D. Bottazzi, R. Montanari, and A. Toninelli, “Context-Aware Middleware for Anyti Anywhere Social Networks,” IEEE Intelligent Systems, vol. 22, no. 5, pp. 23-32, Sep. 2007.

[10] T. Mantoro, “Metrics evaluation for context-aware computing,” in Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia, 2009, pp. 574-578.

[11] J. Ledlie, B. Odero, E. Minkov, I. Kiss, and J. Polifroni, “Crowd translator: on building localized speech recognizers through micropayments,” SIGOPS Oper. Syst. Rev., vol. 43, no. 4, pp. 84-89, Jan. 2010.

[12] Y. Liu, V. Lehdonvirta, M. Kleppe, T. Alexandrova, H. Kimura, and T. Nakajima, “A crowdsourcing based mobile image translation and knowledge sharing service,” in Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia, 2010, p. 6:1--6:9.

[13] A. Wu, X. Yan, and X. (Luke) Zhang, “Geo-tagged mobile photo sharing in collaborative emergency management,” in Proceedings of the 2011 Visual Information Communication - International Symposium, 2011, p. 7:1--7:8.

246246246245