Greenstamp – Mobile Energy Efficiency Services is a research project to develop technologies capable of analyzing and cataloging the energy efficiency of mobile applications integrated into app store processes
Despite the importance that citizens and, by inerence, mobile software promoters companies, give to the energy efficiency of apps, the current app stores, constituting the privileged means of validation and distribution of applications, do not provide consumers with any indication about their energy efficiency, nor the developers action-oriented information on how to improve energy consumption. Indeed, for a consumer to extract any indication of the efficiency of an application available in a mobile market, it can only use the score or comments made by other users, which may include the perception of other users as to their energy performance. However, these ratings and comments, while damaging the reputation of developers and the success of their applications, can result from many other factors, such as functional limitations or interface problems, and are not a viable solution to inform consumers about the efficiency of the applications they are on the verge of installing.
In addition to the fallibility of a classification based on perceptions, this model is clearly distinct from other markets, such as the appliance market, or the automobile, where not only is it mandatory to provide information on energy efficiency of the products marketed, but customers themselves are available to pay more for more energy-efficient products.
It is this incentive that is intended to be added in this project for the huge market for mobile applications, particularly for the companies that develop them and for their consumers, which totalled close to 4 billion globally in July 2019 (a figure that in 2017 was 2.7 billion, which shows that this is a huge and still growing market).
The GreenStamp project aims to investigate and develop techniques and technologies capable of analyzing, cataloging and informing about the energy efficiency of mobile applications and how to optimize it, thus reducing the energy consumption of the mobile market.
This goal is realized in direct impacts on the wide range of citizens who are consumers of apps, mobile application companies and app stores.
Research and development of highly innovative techniques and technologies, unparalleled in the market. They are translated into the following technical-scientific objectives:
- Investigate and conceptualize new systems for the acquisition, processing and analysis of data related to the energy efficiency of mobile applications
- Investigate and conceptualize innovative machine learning mechanisms and cataloging energy consumption patterns of mobile applications based on static and dynamic data
- Investigate and conceptualize ways to information to users about the energy efficiency of apps, and relevant recommendations related to this factor
- Investigate and conceptualize models and mechanisms of technical and action-oriented recommendation to mobile application promoters, on how to optimize this parameter in their products, in an integrated way in their practice
- Investigate and conceptualize a new interface to support decision and system management.
As for app consumers, the impact will be first and foremost on your satisfaction. This will come from the certainty that you can have energy-efficient applications that optimize your device’s resources, rather than having applications that, in some cases you’re usually unaware of at first, drain your mobile device’s limited energy resources with excessive and unnecessary battery consumption.
This certainty will be achieved by providing information on the energy profile of applications at the time of their choice and installation, and also through a system of recommendations to be investigated. Such knowledge will allow consumers to opt for energy-efficient solutions, as is currently the case in other markets (home appliances, automobiles, real estate and others), thereby optimizing the energy performance of their device and increasing the autonomy time of the device.
Thus, a user who chooses efficient applications, will charge their device less often, will have a lower cost on their energy bill and reduce the risk of developing nomophobia with the certainty that the energy consumption of their applications is great.