Project Smart Nest Box (SNBox)

The project Smart Nest Box (SNBox) is a joint project with the Czech University of Life Science Prague, Faculty of Environmental Science (abbreviation ČZU, which origins in its Czech name). SNBox project has run since September 2014 and is ongoing. The Principal Investigator of the SNBox project has been Markéta Zárybnická from ČZU. The CIIRC ČVUT part has been lead by Václav Hlaváč.

SNBox project

The video recording and analysis has become a successful non-invasive method for collecting biological data on different taxa of animals. SNBox has aimed at building a smart sensory rich nesting box and at creating a appropriate methodology for bird nesting video analysis. We pushed the idea forward to the long term surveillance of cavity or box-nesting species. We developed and tested the Smart Nest Box (SNBox) – the system that contains the battery powered computerized device, which overcomes the usual limitations in data storage capacity, power source, and insufficient light. The power conservation was achieved by synchronization of cameras, light sources, and data loggers only to intervals in which the animals are active.

The CIIRC team is responsible for SNBox sensing and computational performance of SNBox. The initial SNBox computer and its software was developed by a Faculty of Electrical Engineering master student Petr Kubizňák in his diploma thesis defended in the study branch Cybernetics and Robotics in June 2014. He has continued SNBox development as a Ph.D. student at ČZU).

ČZU team and Markéta Zárybnická in particular are the SNBox project leaders. They brought in the concept, core design, supervised CIIRC team in its technological activities and use the SNBox.

What was developed?

SNBox serves for monitoring of cavity-dwelling animals and efficient collection of high-quality biological video/audio data. In particular, we created the bird nest continuously monitored by camera system operating in a remote location for a week without replacement of the battery. SNBox enables to set its awake time according to the actual sunset/sunrise timing. SNBox electronics contains a control board with a dual-core processor running two operating systems simultaneously with a 256 MB operating memory and 4 GB memory card (Fig. 1a), a pair of USB monochromatic industrial cameras (1280 x 1024 pixels, up to 10 frames per second) with an infrared 830 nanometres lighting (Fig. 1b), an event detector placed in the SNBox opening (Fig. 1c), a radio-frequency identification (RFID) reader, auxiliary sensors as a microphone, a thermometer, and a 60 Ah 12 V traction battery to power the whole system.


Fig. 1 – Components of the smart nest box (SNBox): (a) the connected and housed control board, placed in the top area of the SNBox; (b) the camera with a lighting board, housed in a box with a transparent cover; (c) infrared light barrier, laid in a shallow groove in the front of the SNBox. During the SNBox application, it was hidden by a thin wooden cover.transparent cover; (c) infrared light barrier, laid in a shallow groove in the front of the SNBox. During the SNBox application, it was hidden by a thin wooden cover.


Fig 2. – (a) Design of the smart nest box (SNBox) and its individual parts: (A) nesting area; (B) electronic area – located in the top part of the box, used for storing the control board; (C) battery area – located on the bottom of the box; and (D) the wiring area – located on the back side of the box. Dimensions are shown in millimetres. (b) Application of the SNBox in the field. Note that most of the outer box surface was covered with aluminium plates and equipped with an extended front plate and a gabled roof to protect against pine marten predation.

We designed the software such that the door camera was activated by the interruption of the IR light barrier to make a 5 seconds recording, while the floor camera started operating right after the door camera and worked for 30-120 seconds based on the user settings. We reduced the trigger speed, i.e. the time delay between disruption of the light barrier by the owl entering the SNBox opening and triggering the first camera frame, to 16 milliseconds. We also designed the system to switch between the sleep and the awake modes. In the sleep mode, the cameras, the light barrier and RFID reader were powered off, while during the awake mode all peripherals were powered on.

Where was SNBox tested?

We applied the SNBoxes to eight Tengmalm’s owl (Aegolius funereus) nests in the Czech Republic during a five-month period. We designed the SNBox as a regular nest box augmented with additional space for embedding all the required components (Fig. 2a). The overall dimensions of the SNBox were 320 × 250 × 820 mm and the weight was 15 kg (without the battery). Most of the outer box surface was covered with the aluminium sheet metal protecting against the nest predation by a pine marten (Martes martes) (Fig. 2b).

What was observed and how was the SNBox technology utilized?

We observed eight owl nests continually during the incubation, nestling, and fledgling phases, in total 309 days, resulting in 3382 owl video events.

The battery conservation was achieved by the periodic switching between the awake and sleep mode according to sunset and sunrise, which varied greatly throughout the breeding season, and which determined activity of owls. The lowest power consumption was found during the mid-summer, i.e. around spring equinox when the night length was about 7.5 hours, and the highest power consumption was in April and August, when the night length was more than 10 hours.

The customised event detector with the unique short trigger speed of 16 milliseconds was quick enough to snap fast moving owls while ignoring the sunlight and insects. The event detector helped to record only actions of interest, which resulted in 1 GB card capacity used in one week. Sufficient reserves of memory card capacity were achieved despite the system using two consecutive cameras. We also applied RFID technology for recognition of the bird parent sex during nesting successfully. The chip reader demonstrated its high potential – it is a simply applicable and cheap tool with a low power consumption for identification of individuals, which regularly visit the same place, in their natural habitat.

What was discovered about Tengmalm’s owl using SNBox?

Twelve types of Tengmalm’s owl activities were observed in total, three of which were not previously documented (Fig. 3).  Video recordings containing unique information on owl nesting were captured (e.g., Video 1). We confirmed that male Tengmalm’s owls deliver most of the prey to the nest, while females incubate the eggs and brood nestlings. Both male and female parents shifted timing of their activities according to sunset and sunrise. Using the SNBoxes, we were able to recognise 98% of all prey items delivered to owl nests as mammals or birds, and to identify 77% of all prey items to family, subfamily, genus or species level (Fig. 3). Moreover, this method allowed us to evaluate the number of prey delivered by the male and the female separately, the proportion of bird adults and nestlings in the diet, as well as the location of the stored prey inside the nest box. In more detailed study, we could also evaluate sibling competition during the stay on the nest.


Fig. 3 – Nesting of Tengmalm’s owl photographed by the camera system of the smart nest box (SNBox): (a) stored prey, eggs and hatchlings in the nest; (b) the female with a shrew (Soricinae) preparing to leave the nest; (c) fledglings at the nest; (d) the male in the SNBox opening giving a prey item (Arvicolinae) to the female; (e) the male in the SNBox opening giving a prey item (Soricinae) to the female; (f) the male in the SNBox opening giving a prey item (bird nestling) to the female.

Finally, we found that the temperature decrease inside owl clutches during female absence was on average 3.2°C and it increased with both the increasing time spent by the female outside the nest and the decreasing outdoor temperature. As a result, female parents reduced the time spent away from the nest with decreasing outdoor temperature, suggesting that the heat losses from the clutch are a limiting factor for Tengmalm’s owl.

What is the future prospect and the perspectives of the SNBox?

The SNBox technology can be easily adjusted for research on other animal species. Specifically, one could simply change the user system configuration by adjusting the awake/sleep time, depending on activity pattern of monitored species. Modifications to the software would allow a deep system adjustment. Replacing the individual hardware components would enable the system to monitor many other tasks. As a result, the system could be used for both diurnal and nocturnal animals breeding in nest boxes or bigger cavities, as well as for research on other animals, in which the action of interest is triggered by actively crossing a specific spot.

The most expensive part of the system for monitoring the Tengmalm’s owl nests was the pair of industrial cameras, which were necessary to collect the required data and which allowed high quality video recordings. We suggest the use of cheaper cameras could reduce the system cost to two-thirds of the actual non-profit price of €1000. Moreover, the system further development might bring significant improvements, including audio recording, Wi-Fi connectivity, online video transmission, and self-acting setting of the awake/sleep time of the system depending on the outdoor light intensity.

We believe the system can be applied to birds, mammals or reptiles using nest boxes to breed, roost, hibernate, or store food so as to monitor their activities and circadian rhythms, feeding ecology, parental care, or sibling competition. Additionally, the modification of sensitivity of the event detector would allow monitoring of insects using cavities and nest boxes. We believe this monitoring system will provide unique insights into the lives of cavity-dwelling animals, as we show by results of the present study on Tengmalm’s owl.

We are ready to start cooperation based on SNBox technology. If there is a demand for more units, we could mediate its production.

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References and links

  • Markéta Zárybnická, Petr Kubizňák, Jiří Šindelář and Václav Hlaváč:Smart nest box: a tool and methodology for monitoring of cavity-dwelling animals, Methods in Ecology and Evolution, published online: 15 Dec 2015, DOI: 10.1111/2041-210X.12509, impact factor 6.554.
  • Markéta Zárybnická,
  • Videos related to SNBox

Responsible: Václav Hlaváč