1. SafePASS Smart Lifejacket – Haptic and Audio Navigation

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SafePASS has designed, implemented and tested the Smart Lifejacket for location-based information and passenger evacuation support. In June 2022 a validation campaign was conducted at NTUA premisses with the help of volunteers where, amongst others, the Smart Lifejacket was tested. The tests that took place were based on a dummy scenario where the research participants, had to follow an evacuation route from “Deck 3” to “Deck 4” due to a fire and smoke incidents. Two floors of the Computer Center at the NTUA campus and the staircase were chosen to represent the real cruise ship’s Deck 3 and Deck 4 area.

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The SafePASS indoor localization module comprises of the Bluetooth Low Energy (BLE) and the Ultra-Wide Band (UWB) technology. For the Smart Lifejacket, the UWB technology is used. While the BLE technology provides room-level accuracy (5 to 10 m), UWB provides sub-meter level accuracy. 

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For the execution of the validation test, first the UWB anchors were installed to cover the test area, and tests were conducted to optimize the indoor localization system. In particular, the UWB anchors were placed 10 centimeters away from the wall using 3D-printed stands, thus reducing signal interference, and improving the location accuracy.

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The volunteers were informed about the SafePASS project, the scope of the validation test, their role acting as passengers during an evacuation scenario, and the smart technologies to be used during the tests. In addition, information about personal data handling and GDPR rules was provided, and consent forms were filled in by those willing to participate.

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Once the volunteers wore the Smart Lifejacket, the lifejacket was activated via the magnetic switch providing real-time location information of the volunteers, as expected. When the evacuation order was initiated, the volunteers were asked to push the navigation button, which is attached on the lifejacket. This action triggered the route request from the SafePASS System (Core Engine) and the subsequent response. After parsing the route, the lifejacket using a series of haptic cues, guided the volunteers along the route until the end of the route was reached. The haptic navigation route is perceived by the volunteers as a series of vibration signals triggered by the haptic actuators:

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• activate the left actuator to signal a left turn

• activate the right actuator to signal a right turn

• activate both actuators to signal a forward movement

• activate the right actuator twice to signal a 180-degree turn

• activate the left actuator and the right to signal upwards movement

• activate the right actuator and then the left to signal downwards movement.

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The navigation algorithm implemented takes into account the passenger location, the speed vector and acceleration, and the angle between the passenger’s speed vector and the next point in the route.

The following pictures provide some insights about the Smart Lifejacket and the validation campaign conducted.

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Regarding the validation of the Smart Lifejacket’s audio navigation feature, additional tests were carried out here. Τhe participants were walking in the area with the wired earplug on the ear while audio instructions were played through the dedicated Chatbot Application, which is a hardware device mounted on the Smart Lifejacket and provides audio instructions to passengers regarding their route towards the designated evacuation exit.

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During the afore-mentioned validation tests, the audio instructions produced by the Chatbot Application had been broken down to simple audio tracks which corresponded to small sections of the entire evacuation route. A specific evacuation scenario was tested (Scenario 3) which included 4 audio tracks (steps 1-4) which had been pre-recorded in both English and French language. In this case, the participant could listen to the audio instructions while walking around the areas, and the audio tracks depended on his/her location in the area, as defined by the Smart Lifejacket’s UWB component which received signals from the deployed UWB anchors.

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In case the passenger desired to change the default language (i.e. English) to another (i.e. French was only supported at the time), then he/she had to push repeatedly for 2-3 seconds the earplug’s button and then speak some key words of the new language. The Chatbot Application could then process the voice message and find the new requested language, which was then the one used for audio instructions through the corresponding tracks’ playback to the participant.

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2. SafePASS Passenger Mobile App

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Regarding the validation of the Passenger Mobile App developed by TEL, an additional small-scale integration test and scenario execution was carried out at the same Computer Center building at the NTUA campus. Particularly, the evacuation route of Scenario 1 was selected as the most representative scenario for an evacuation situation. Specifically, two decks at NTUA campus have been chosen to represent the real cruise ship’s Deck 3 and Deck 4, which had been used for the execution of Scenario 1 using the Mobile App. Along this evacuation route, BLE beacons were placed at specific locations in order to sufficiently cover the area from the starting point (corridor in Deck 3 – ground floor at the NTUA building) to the exit (Club area in Deck4 – 1st floor at the NTUA building).

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In this case, the Passenger Mobile App was tested by the volunteers using the pre-selected Scenario 1, during which the Mobile App was constantly guiding the volunteer point-by-point towards the indicated evacuation exit, while providing visual and textual message on the screen.

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A major part of the Mobile App’s functionality was the localization engine running on the mobile device, which could determine the volunteer’s location in the areas using 3 different ways which were implemented using 3 different technologies:

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• automatic location estimation using the deployed BLE beacons (provide 5-10m accuracy)

• manual selection of the location by the volunteer on the device screen’s map

• automatic determination of the location by scanning QR codes on the walls

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During the integration tests, the SafePASS server was utilized where all the required components, i.e. SafePASS Core Engine and Core Platform, were already deployed and operating. In this way, the Mobile App itself, connected through the Mobile Backend which is also installed on the Core Platform, could have direct connection to different SafePASS components and thus exchange all required messages with them, including the following:

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• Core Engine: reception of the evacuation status (ON) and the active evacuation route

• Mobile Backend: log-in process of the user to the Passenger Mobile App

• Core Platform: periodic automatic transmission by the Mobile App of the user’s location and the transmission of the passenger’s assistance requests when the volunteer pushed the relevant button in the Mobile App

 

After concluding all induvial validation campaigns and tests for the smart lifejacket and passenger mobile app, feedback was collected to evaluate the functionalities demonstrated, while useful ideas and recommendations for potential future developments were provided.

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