Project Details
Description
"She has fallen." This short sentence can entail dire consequences, especially among the older part of the population. In cases where a person lives alone and falls seriously enough to not being able to get up or help themselves, the
outlook for help is far and can in worse case be fatal. Even if no physical injury has occured, the person may not be able to stand up again, which in term can lead to serious injuries, both physically aswell as mentally.
This project seeks to contribute to the remedy of this problem, by development of a smart-device that by means of Machine Learning will be able to detect people that have fallen and automatically alert the caretaker or the relatives.
The product is designed to function away from home by the help of a LoRaWAN networksetup. The system is fully automatic, so alarmmessege will be sent independently of user interaction in case of for example unconsciousness.
Furthermore the product will include a GPS, so that the person who has fallen, will be able to be localized precisly
The report will describe the development of a limited part of the system AFDS. In the project the focus has been put on the user's wearable device. There has furthermore been focused on the private setup of LoRaWAN for the backend
system, that receives the alert messages and localizes the user.
AFDS ends up as a system, that can detect falls of dierent types with a high precision and externally inform about the alarm together with its geolocation through LoRaWAN
Not all the requirements setup for the system are fullled, but the product is a proof of concept. This is seen through the testing that has been done. Finally there will be presented suggestions for future work for AFDS.
outlook for help is far and can in worse case be fatal. Even if no physical injury has occured, the person may not be able to stand up again, which in term can lead to serious injuries, both physically aswell as mentally.
This project seeks to contribute to the remedy of this problem, by development of a smart-device that by means of Machine Learning will be able to detect people that have fallen and automatically alert the caretaker or the relatives.
The product is designed to function away from home by the help of a LoRaWAN networksetup. The system is fully automatic, so alarmmessege will be sent independently of user interaction in case of for example unconsciousness.
Furthermore the product will include a GPS, so that the person who has fallen, will be able to be localized precisly
The report will describe the development of a limited part of the system AFDS. In the project the focus has been put on the user's wearable device. There has furthermore been focused on the private setup of LoRaWAN for the backend
system, that receives the alert messages and localizes the user.
AFDS ends up as a system, that can detect falls of dierent types with a high precision and externally inform about the alarm together with its geolocation through LoRaWAN
Not all the requirements setup for the system are fullled, but the product is a proof of concept. This is seen through the testing that has been done. Finally there will be presented suggestions for future work for AFDS.
| Status | Finished |
|---|---|
| Effective start/end date | 03/02/2020 → 27/05/2020 |
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