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Raspberry Pi Based IoT System for Bats Detection at Wind Farms
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences. (Group 7)
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences. (Group 7)
2020 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Context: Large numbers of bats are killed by collisions with wind turbines and there is at present no accepted method of reducing or preventing this mortality. We designed a system, which detects and records any bats’ activity in and around the surroundings of wind turbines. The system can help to study bats by identifying the species that are present in that particular locality.

Objectives: The main objective of this thesis is to design an ultrasound-based IoT system, which detects the bats to prevent them from clashing with wind turbines. The design is based on a study of bats’ behaviors.

Methods: The system has been developed using User-Driven Design, UDD, approach. The required functionalities have been embedded into IoT based system. An ultrasonic technology along with other sensors are used. The sensors are intended to activate monitoring during favorable conditions for bat activity.

Results: A model of a system has been developed. The model was implemented into a prototype. Recorded bats’ activities are uploaded to a server by employing a suitable app, which informs the user about the activities of bats' various sub-species.

Conclusions: A surveillance for bats approaching the wind farms within 80 m has been developed. The monitoring system is activated when the weather conditions are favorable for bat activities.

Place, publisher, year, edition, pages
2020. , p. 82
Keywords [en]
Bats, Pattern Recognition, Ultrasonic Frequencies, Ultrasonic Microphone, Ultrasonic Transducer, Wind Turbines
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:bth-20899OAI: oai:DiVA.org:bth-20899DiVA, id: diva2:1514905
External cooperation
Bioseco
Subject / course
ET1464 Degree Project in Electrical Engineering
Educational program
ETGDB Bachelor Qualification Plan in Electrical Engineering 60,0 hp
Presentation
2020-06-17, 12:35 (English)
Supervisors
Examiners
Available from: 2021-01-08 Created: 2021-01-07 Last updated: 2021-01-08Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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