The objective of precision beekeeping is to minimize resource consumption and maximize productivity of bees. This is achieved by detecting and predicting beehive states by monitoring apiary and beehive related parameters like temperature, weight, humidity, noise, vibrations, air pollution, wind, precipitation, etc. These parameters are collected as a raw input data by use of multiple different sensory devices, and are often imperfect and require creation of correlation between time data series. Currently, most researches focus on monitoring and processing each parameter separately, whereas combination of multiple parameters produces information that is more sophisticated. Raw input data sets that complement one another could be pre-processed by applying data fusion methods to achieve understanding about global research subject. There are multiple data fusion methods and classification models, distinguished by raw input data type or device usage, whereas sensor related data fusion is called sensor fusion. This paper analyses existing data fusion methods and process in order to identify data fusion challenges and correlate them with precision beekeeping objectives. The research was conducted over a period of 5 months, starting from October, 2019 and was based on analysis and synthesis of scientific literature. The conclusion was made that requirement of data fusion appliance in precision beekeeping is determined by a global research objective, whereas input data introduces main challenges of data and sensor fusion, as its attributes correlate with potential result.
Smart city is commonly described as "city for citizens" empowering citizen lives by implementing methods of smart economy, smart environment and smart mobility, all aimed to address such concerns as resource scarcity, air pollution, citizens health and traffic problems. These methods are usually implemented in invisible-to-citizen ways. To address previously mentioned concerns different requirements and guidelines are introduced. One of such concerns is citizens' commute, so corresponding requirements must be defined according to modern smart city goals, i.e., to be economically reasonable and beneficial, and should promote clean environment. The problems that arise are related to selection of proper transportation means for commute purposes. Aim of this paper is to propose a model for economic comparison of commute by use of different transportation means within the city taking into account person's wage.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.