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Baterije se v primerjavi s preostalo strojno opremo razvijajo mnogo počasneje, zato je pomembna njihova učinkovita raba. Predlagamo sistem, ki izkoristi sposobnosti pametnih telefonov za zaznavanje in glede na uporabnikov kontekst prilagodi kakovost videa, ne da bi pri tem zmanjšal zadovoljstvo uporabnika. Z laboratorijskimi meritvami dokažemo, da je posledica boljše kakovosti videa večja poraba električne energije. Z nenadzorovanim eksperimentom smo raziskali vpliv med uporabnikovo fizično dejavnostjo in njegovo percepcijo videa. V ta namen smo razvili aplikacijo, ki zajema podatke o uporabnikovi fizični aktivnosti in njegovi izbiri ločljivosti videa. Naknadna nadzorovana študija je dodatno potrdila ugotovitve o vplivu fizične aktivnosti na percepcijo videa. Odkrili smo, da bi predlagana rešitev prihranila najmanj štiri odstotke baterije dnevno. Izpostavili smo možnosti uporabe približnega računanja in utemeljili zakaj bi bilo potrebno zaznavanje razširiti na širši kontekst. Batteries are developing much slower compared to other computer hardware, therefore it is important to use them efficiently. We proposed a system that takes advantage of smartphones' sensing possibilities, and based on user context adapts video quality without lowering user experience. With rigorous measurements we proved that better video quality results in higher energy consumption. With an unsupervised experiment we explored the relationship between user's physical activity and their video perception. In order to carry out such an experiment, we developed an application which collects data about user's physical activity and the desired video decoding quality. Additional supervised experiment further confirmed our findings on the relation between physical activity and video perception. We found that the proposed solution would save at least four percent of the battery charge per day. We discussed the potentials of approximate computing techniques and explained the need to further expand context sensing. |
