0000000000116390

AUTHOR

Olli Vaananen

showing 4 related works from this author

Predictive pumping based on sensor data and weather forecast

2019

In energy production, peat extraction has a significant role in Finland. However, protection of nature has become more and more important globally. How do we solve this conflict of interests respecting both views? In peat production, one important phase is to drain peat bog so that peat production becomes available. This means that we have control over how we can lead water away from peat bog to nature without water contamination with solid and other harmful substances. In this paper we describe a novel method how fouling of water bodies from peat bog can be controlled more efficiently by using weather forecast to predict rainfall and thus, minimize the effluents to nature. peerReviewed

0209 industrial biotechnologyInternet of thingsPeat0208 environmental biotechnologyWeather forecastingopen data02 engineering and technologycomputer.software_genrevesistöjen säännöstely020901 industrial engineering & automationLead (geology)Extraction (military)esineiden internetWater pollutionEffluentavoin tietota218turvetuotantota113Foulingta213Environmental engineeringhallintajärjestelmätsäänennustus020801 environmental engineeringWater resourcesälytekniikkaEnvironmental sciencecomputerrain predictionpredictive control
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Requirements for Energy Efficient Edge Computing: A Survey

2018

Internet of Things is evolving heavily in these times. One of the major obstacle is energy consumption in the IoT devices (sensor nodes and wireless gateways). The IoT devices are often battery powered wireless devices and thus reducing the energy consumption in these devices is essential to lengthen the lifetime of the device without battery change. It is possible to lengthen battery lifetime by efficient but lightweight sensor data analysis in close proximity of the sensor. Performing part of the sensor data analysis in the end device can reduce the amount of data needed to transmit wirelessly. Transmitting data wirelessly is very energy consuming task. At the same time, the privacy and s…

hajautetut järjestelmätBattery (electricity)energiatehokkuusbusiness.industryComputer science020206 networking & telecommunications020207 software engineering02 engineering and technologyEnergy consumptionEncryptionedge computing0202 electrical engineering electronic engineering information engineeringWirelessEnhanced Data Rates for GSM EvolutionbusinessEnergy (signal processing)Edge computingComputer networkEfficient energy use
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LoRa-Based Sensor Node Energy Consumption with Data Compression

2021

In this paper simple temporal compression algorithms' efficiency to reduce LoRa-based sensor node energy consumption has been evaluated and measured. It is known that radio transmission is the most energy consuming operation in a wireless sensor node. In this paper three lightweight compression algorithms are implemented in an embedded LoRa platform to compress sensor data in on-line mode and the overall energy consumption is measured. Energy consumption is compared to the situation without implementing any compression algorithm. The results show that a simple compression algorithm is an effective method to improve the battery powered sensor node lifetime. Despite the radio transmission's h…

Consumption (economics)Battery (electricity)Computer sciencebusiness.industrySensor nodeReal-time computingWirelessEnergy consumptionbusinessComputer Science::Operating SystemsWireless sensor networkEnergy (signal processing)Data compression2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)
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Compression Methods for Microclimate Data Based on Linear Approximation of Sensor Data

2019

Edge computing is currently one of the main research topics in the field of Internet of Things. Edge computing requires lightweight and computationally simple algorithms for sensor data analytics. Sensing edge devices are often battery powered and have a wireless connection. In designing edge devices the energy efficiency needs to be taken into account. Pre-processing the data locally in the edge device reduces the amount of data and thus decreases the energy consumption of wireless data transmission. Sensor data compression algorithms presented in this paper are mainly based on data linearity. Microclimate data is near linear in short time window and thus simple linear approximation based …

Edge deviceenergiatehokkuusWireless networkComputer sciencesensoriverkot020206 networking & telecommunications02 engineering and technologyEnergy consumptioninternet of thingscompression algorithmedge computingalgoritmit0202 electrical engineering electronic engineering information engineeringElectronic engineeringesineiden internet020201 artificial intelligence & image processingLinear approximationEdge computingEfficient energy useData compression
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