Abstract
Recently, the demand for monitoring a certain object covering large and dynamic scopes such as wildfires, glaciers, and radioactive contaminations, called large-scale fluid objects (LFOs), is coming to the fore due to disasters and catastrophes that lately happened. This article provides an analytic comparison of such LFOs and typical individual mobile objects (IMOs), namely animals, humans, vehicles, etc., to figure out inherent characteristics of LFOs. Since energy-efficient monitoring of IMOs has been intensively researched so far, but such inherent properties of LFOs hinder the direct adaptation of legacy technologies for IMOs, this article surveys technological evolution and advances of LFOs along with ones of IMOs. Based on the communication cost perspective correlated to energy efficiency, three technological phases, namely concentration, integration, and abbreviation, are defined in this article. By reviewing various methods and strategies employed by existing works with the three phases, this article concludes that LFO monitoring should achieve not only decoupling from node density and network structure but also trading off quantitative reduction against qualitative loss as architectural principles of energy-efficient communication to break through inherent properties of LFOs. Future research challenges related to this topic are also discussed.
Highlights
With an increasing number of various sensor devices connected to the Internet, it is possible to obtain the infrastructural and environmental data that would enable efficient approaches to perceive and manage urban facilities [1]
Previous studies [4,5] typically assume that events or phenomena are generated by individual mobile objects (IMOs) such as vehicles, people, and animals
The survey on object monitoring technologies and strategies come up with for IMOs is first fulfilled; a technological evolution model with three phases is conducted to evaluate the presence of technological advances for large-scale fluid objects (LFOs) monitoring
Summary
With an increasing number of various (wireless) sensor devices connected to the Internet, it is possible to obtain the infrastructural and environmental data that would enable efficient approaches to perceive and manage urban facilities [1]. Monitoring of a different type of object, such as bio-chemical materials, radioactive contaminants, and wildfires, is receiving attention and its demand is increasing more and more thanks to recent big disasters and catastrophes, e.g., forest fires in Greece, massive fires throughout California in the United States, and Japan’s earthquake and radiation leaks Such objects widely cover a sensor field and it may dynamically change its own shapes due to physical environments such as wind, geographical features, and so on. An IMO is referred to as a point whereas an LFO might be shown as a large/dynamic two-dimensional diagram because the LFO covers a wide field and it could dynamically alter its own shapes In other words, such different characteristics of an LFO compared with an IMO hindered direct utilization of ideas that have been proposed for energyefficient data dissemination for IMOs. it was forced to design novel energy-efficient data delivery schemes. Based on these investigations, this article addresses future research challenges to break through for accomplishing high energy efficiency and high quality of user experience through interoperation with state-of-the-art IoT technologies such as energy harvesting [8], IoT analytics [9], dynamic clustering [10], Web-based IoT [11], etc
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