Fuzzy power management for environmental monitoring systems in tropical regions

Watts, Asher G.; Prauzek, Michal; Musilek, Petr; Pelikán, Emil; Sánchez‐Azofeifa, Arturo

doi:10.1109/ijcnn.2014.6889844

Cited by 13 publications

(9 citation statements)

References 15 publications

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“…On the other hand, WSN testing under real conditions requires construction of hardware prototypes and significant amount of time so that the system can be exposed to various environmental conditions possible during actual deployment (this requires a minimum of one full year for most environments). This is further exacerbated by the large variety of possible deployment environments [37,145]. These limitations will require further improvement of simulation tools and sophisticated modeling of dynamic deployment environments Table 1 Classification of nature-inspired applications in wake-up scheduling according to their role within the communication layer stack [29].…”

Section: Future Directions and Open Issuesmentioning

confidence: 99%

Review of nature-inspired methods for wake-up scheduling in wireless sensor networks

Musilek

Krömer

Bartoň

2015

Swarm and Evolutionary Computation

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Section: Future Directions and Open Issuesmentioning

confidence: 99%

Review of nature-inspired methods for wake-up scheduling in wireless sensor networks

Musilek

Krömer

Bartoň

2015

Swarm and Evolutionary Computation

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“…The aim of the fuzzy energy management is to avoid system shutdowns, to maintain the duty cycle and the PDeS 2015May 13-15, 2015. Cracow, Poland battery as high as possible, keeping the data buffer at a low level, and reducing the wasted energy.…”

Section: Fuzzy Logic Algorithmmentioning

confidence: 99%

“…Generally, EMSs can be deployed under various climatic conditions characterized by different daily and seasonal cycles of environmental energy availability , Watts et al (2014)). Here, the environmental energy is meant solar energy.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Energy Management of Autonomous Weather Station∗∗This work was supported by project SP2015/154, Development of algorithms and systems for control, measurement and safety applications. of Student Grant System, VSB-TU Ostrava.

Prauzek

Konecny

Hamel³

et al. 2015

IFAC-PapersOnLine

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The importance of renewable energy is increasing rapidly nowadays. Solar energy is one of the most powerful resources that can be used to provide power supply for remote electrical devices. Such remote devices often need batteries replacements and maintenance that raises expenses. This contribution describes energy management and power harvesting implementation in a low-power microcontroller integrated within an autonomous solar-powered device with supercapacitor that significantly reduces maintenance needs. The energy management implements a fuzzy logic-based system that allows it to adapt to ambient temperature and sunlight intensity in deployment location. Fuzzy energy management sets device's functional mode that affects the measurement rate of the weather station and subsequent storage rate in SD Card. Both simulation results and real data results obtained in a laboratory located in Ostrava, Czech Republic, are presented in this contribution.

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“…secondary batteries or supercapacitors) and reserve energy supplies (primary batteries). In addition, EMSs can be deployed under various climatic conditions [2], [3] characterized by different daily and seasonal cycles of environmental energy availability.…”

Section: A Autonomous Nodes and Energy Harvestingmentioning

confidence: 99%

Fuzzy algorithm for intelligent wireless sensors with solar harvesting

Prauzek

Musílek

Watts

2014

2014 IEEE Symposium on Intelligent Embedded Systems (IES)

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Wireless sensors are sophisticated embedded systems designed for collecting data on systems or processes of interest. In many cases, they are expected to operate in inaccessible locations, without user supervision. As a result, such monitoring systems need to operate autonomously and independently of external sources of energy. To achieve long-lived sustainability, monitoring systems often rely on energy extracted from the environment, e.g. through solar harvesting. Their design is a challenging problem with several conflicting goals and a number of design and implementation possibilities. For obvious reasons, these devices must be designed in an energy efficient way. As a result, they usually have low computational performance and cannot implement complicated control algorithms. At the same time, due to the requirements for autonomy and dependability, they must be endowed with certain degree of adaptability and fault tolerance -properties typically found in intelligent systems. In this contribution, we describe the design flow of an intelligent embedded control system for management of energy use in wireless monitoring systems. The paper also provides a simulation-based analysis of the control system performance.

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Fuzzy power management for environmental monitoring systems in tropical regions

Cited by 13 publications

References 15 publications

Review of nature-inspired methods for wake-up scheduling in wireless sensor networks

Review of nature-inspired methods for wake-up scheduling in wireless sensor networks

Fuzzy Energy Management of Autonomous Weather Station∗∗This work was supported by project SP2015/154, Development of algorithms and systems for control, measurement and safety applications. of Student Grant System, VSB-TU Ostrava.

Fuzzy algorithm for intelligent wireless sensors with solar harvesting

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