SAMS -- Smart Apiculture Management System

About

Beekeeping with small-scale operations provides perfect innovation labs for demonstration and dissemination of cheap and easy-to-use open source ICT applications in developing countries.

The SAMS Project – SAMS Project

Abstract

Overview

Future development in beekeeping has proved to be successful by implementing smart apiary management services that use information communication and technology (ICT) based on remote sensing tools for monitoring honybee colony health and productivity.

The aim of Smart Apiculture Management Services (SAMS) is therefore, to develop an open source ICT technology that allows active monitoring and managing of bee colonies to ensures bee health and bee productivity. It also answers the requirements of beekeeping in different countries and settings, for sustainable agriculture worldwide.

SAMS reduces the risks of depleting honey production that threatens livelihoods of beekeepers and degradation of pollination power of suffering bee colonies that threats overall agricultural production. It also simplify bee management while creating the possibility to understand the behaviour of bees and the environmental aspect better to ensure food production and bee farming activities.

The outcome of SAMS

are

a) A physical low-cost beehive model and integrated open source sensor and information transition technology, as well as energy-supply solution;

b) A decision support system that combines the sensor-based data-outputs with other information sources and predictive models to measure, analyse and describe different states of the bee colony such as health, vitality and production;

c) An automatic advisory support tool, which will alert the beekeeper in an easily understandable way if any aberrations from normal states are metered and will provide advice on appropriate countermeasures and

d) A bee management business concept for the local production and up-scaled implementation of the developed beehives with integrated beehive monitoring system. These outcomes overcome country-specific challenges of beekeeping and simplify the management to ensure better production resulting in creating jobs (particularly youths/ women), triggering investments and knowledge exchange networks.

http://article.sciencepublishinggroup.com/pdf/10.11648.j.ijast.20190302.11.pdf

Resources


SAMS - Smart Apiculture Management Services (@SAMS_EU_H2020) | Twitter

1 Like

Sounds nice. Thanks for sharing.

The people behind

Looks like people from the University of Kassel (UNIKAS) are the lead developers of the SAMS Hive System, while data will be stored at the University of Latvia (UNILV), where the predecessor project “ITAPIC” took place.

Some collected information

… of the published papers and reports so far.

Initial Data Management Plan

Low-fidelity HIVE Prototype Design

https://sams-project.eu/wp-content/uploads/2019/02/D.3.2_Low-fidelity-HIVE-prototype-design_Report.pdf

Diese feature-(Wunsch-)Liste kommt mr irgendwie bekannt vor, code gibt es public!!

For the Raspian Jessie Lite operating system of the SBC Raspberry Pi 3, a script was written which addresses the sound card and converts the audio signals of the microphone. These signals are further broken down into their frequency components by means of a Fast Fourier Transformation (FFT) and written to a text file as numerical values. Using Wi-Fi and a GSM module, the files are uploaded to a web server and then deleted from the SBC memory.

In case, radio transmission is not possible, the data remains on the device memory until a connection is established. Conversely, the SBC can also receive updates via the server. This means that settings, such as the intervals of the data logger, can be changed from any computer with Internet availability. In addition to the interval sizes for updates and uploads, variables that can be changed include the recording length of the audio signals and the sampling or sampling rate. The main contents of the Python code can be found in Appendix II or are open-source fully available on the Internet on the Github developer platform at GitHub - y0va/hummingpy: Python sound spy on RPI3 for bee hives.

Interessant finde ich, dass sie sich bei der Sound-Analyse auf die unteren Frequenzen beschränken.

several main frequency ranges could also be identified, which are related to the typical basic humming of a bee colony and the increase and decrease of the wing beat frequencies. The main frequency ranges there are between 100-150 Hz and 200-250 Hz.

Was sie im Text mit ArduinoNano meinen ist mir nicht ganz klar, von den Abbildungen her ein klassischer ATmega328P, Arduino vermarktet aber neuerdings den “Nano” auch mit Cortex M4 oder auch Cortex M0-Prozessoren (dann mit “33” im Namen), teilweise mit onboard Micro (“Sense” im Namen). Ist ein eigener thread wert!