Adopting incentive mechanisms for large-scale participation in mobile crowdsensing: from literature review to a conceptual framework

R. I. Ogie

doi:10.1186/s13673-016-0080-3

Human-centric Computing and Information Sciences

Table 1 SPECTRUM applied to real-world mobile crowdsensing applications

From: Adopting incentive mechanisms for large-scale participation in mobile crowdsensing: from literature review to a conceptual framework

Mobile crowdsensing application	Socioeconomic factors	Privacy	Effort	Commercial-interest	Term	Requirements	Usefulness	Money	Type of incentive adopted
Mobile crowdsensing application	Will participants’ social or economic needs be met?	Is there high privacy risk?	Is the effort required generally considered to be high, low, moderate?	Is there a business interest or motive to profit financially?	Is the term long, short, or seasonal?	Is there a strict requirement in terms of data quality, quantity, or area coverage?	How beneficial is the collected data to the general public?	How well is money or other available resources a limiting factor?	Type of incentive adopted
BudBurst Mobile [109]	Yes, social interactions with other users	Moderate	High	No	Seasonal	Area coverage	Understanding the effects of global climate change	Not discussed; implied	Gamification i.e. floracaching game; altruistic contribution to scientific knowledge of plant’s life cycle
Waze [110]	Yes, social needs are met through gaming entertainment; economic through time and gas money savings in traffic	High	Low	Yes	Long term	No	Helping citizens save time and gas money on their daily commute through road traffic	Not discussed; implied	Gamification; other social incentives such as increased reputation in community, savings on fuel when commuting
NoiseMap [111]	Yes, need for a serene urban environment; social interactions with other users	Moderate	Moderate	No	Long term	Quality and quantity	Monitoring of urban noise pollution	Not discussed; implied	Social i.e. ranking of participants according to contributions
NoiseTube [112]	Yes, need for a serene urban environment	Moderate	Moderate	No	Long term	No	Monitoring of urban noise pollution	Not discussed; implied	Social i.e. altruistic contribution to local environment
NoiseSPY [113]	Yes, need for a serene urban environment	Moderate	Moderate	No	Long term	No	Monitoring of urban noise pollution	Not discussed; implied	Social i.e. altruistic contribution to local environment
Crowdsignal and Algosnap [114]	Yes, economic reward	Low–High	Low–High	Yes	Short–long term	Quality, quantity and area coverage	Data for academic research	Reward is based on budget and task	Monetary
Premise [115]	Yes, economic reward	Low–High	Low–High	Yes	Short–long term	Quality, quantity and area coverage	Data used by private companies and partners	Reward is based on budget and task	Monetary
GasMobile [116]	Yes, need for cleaner city	Moderate	Low	No	Long term	Quality	Monitoring of urban air pollution	Not discussed; implied	Service i.e. Information feedback
Ikarus [117]	Yes, through paragliding sport.	No	Moderate	No	Long term	Not a necessity	Sensed data is used to create thermal map for the paragliding community	Not discussed; implied	Social i.e. increased reputation in the paragliding community
LiveCompare [118]	Yes, grocery shoppers save money on purchase	Moderate	Moderate	No	Long term	No	Only participating grocery shoppers save money on purchase	Not discussed; implied	Service i.e. grocery bargain hunting

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