Introduction: Raízes: O Desafio

The idea is a gamification of path, making the visitation of the locality more attractive and immersive for tourists. Scattered totems, which were thought shall forward the challenges along the way, in a sequence of activities to be carried out. This totem will be blocked until the Group hit the reply. When he shoots, the totem is unlocked and people are directed to the next totem.


Carlos Henrique Caloete Pena -

Cora Lima Sales -

Eduardo Augusto de Andrade Pereira-

Ewerton Lucas Ramos do Espirito Santo -

Iraline Nunes Simões -

Jade Torres Jofilsan -

Larissa de Oliveira Lages -

Raphael Henning de Souza -

Step 1: Components Used and Prices

In this project, main items used were:

->Mfrc522 Mifare RFID Reader Module Kit around R$35,00

->Logitech HD Pro Webcam C920 around R$260

->DragonBoard 410c + mezanino around R$400

The project will consist of an RFID sensor, in which it will be used to start and close a game, a camera, in which it will capture the image of the object inserted in the compartment and identify if the object inserted in the compartment is the correct object for move on to the next mission.

Step 2: Story Flowchart

We see the flow of one of the stories that can be told about the island. The group of visitors arrive in totem 1, which is where the challenge will be initialized and a photo is taken to count the number of members of the group. After being given the start, the group of visitors receive a mission, in which it will be necessary to be fulfilled to go to the next challenge. This will require a greater interaction of visitors with the island and its inhabitants. When the group of visitors complete their last mission, the photo taken at the beginning of the challenge will be shown, the person in charge will close the challenge and the group of visitors will be sent to the museum.

Step 3: Using the Camera

The aim of the camera is to detected a specific object, using its color. We use the openCV with python to achieved this. We used the function cv2.inRange to perform the color detection. We defined lower and upper limits for the range of the wished color. After calling cv2.inRange, a binary mask is returned, where white pixels (255) represent pixels that fall into the range and black pixels (0) do not. The object will be positioned in a fixed place, thus the code count the number of pixels that are inside the range. After that the number is compared with a pre-defined range to verify if the color is correct.

Step 4: Using RFID

It was quite difficult to use RFID because spi communication was not enabled for the dragonboard. So, we decided to use the mezzanine. When using, we encountered another problem while downloading the arduino IDE, since none of the official site links were working, so we had the option of using 'apt-get install arduino', which has an outdated version, which does not support The RFID library. To solve all these problems, it was necessary to downgrade the RFID library 1.3.5 and use a version that was converted to pure C.

Step 5: References and Code

Mangrove forests’ importance and potential for smart cities -


Innovation and action for forests -

Um caso emblemático do direito à moradia conquistado em área de risco legalmente preservada -

Aspectos etnoecológicos da carcinicultura no parque dos manguezais e ilha de deus -

O Processo de Adensamento Populacional em Áreas de Manguezais: o caso específico da Ilha de Deus -

VÍDEOS “descobrindo o sururu” 2015 “quando a maré encher - doc” 2015 "Viveiros da Ilha de Deus Uma Questão Social" 2010

“Mangue: moderno, pós-moderno,global” -

Step 6: Cloud-based Communication

Cloud-based services were used to leverage even more the power of the Dragonboard for connecting the totems and storaging data about visits. For that, MongoDB, ExpressJS and Node.js were used for this communication, where the processing of images and data gathered by sensors is done by the board. Express did the routing for pages and REST API for CRUD operations in the database.

The tour starts when the RIFD card is put in contact with the first totem in the curcuit. This action creates a register in the bank ("Visit") that has fields for: start (start time of the tour), number of people (from face detection using Cascade), favourite part of the journey, fields for defining if the group of tourists completed each of the tasks assigned and a field with the end time of the journey.

Regarding video and imagery data, all the processing is done by the board, while the output is sent to the database. Informations such as number of people in each visit (gathered by face detection), confirmation of object detection and in the future, emotions detection for measuring satisfaction during touristic activities.


Swansong (author)2017-07-23

Thanks for sharing :)