TY - JOUR
T1 - Li-Tect: 3D Monitoring and Shape Detection using Visible Light Sensors
AU - Jarchlo, Elnaz Alizadeh
AU - Tang, Xuan
AU - Doroud, Hossein
AU - Jimenez, Victor P. Gil
AU - Lin, Bangjiang
AU - Casari, Paolo
AU - Ghassemlooy, Zabih
PY - 2019/2/1
Y1 - 2019/2/1
N2 - In this paper, we propose Li-Tect, an algorithm to detect the shape of an object located in an indoor environment using low cost optical elements through sensing the environment's light. The algorithm analyzes, relying on the predictability of optical propagation paths, how much light is expected to propagate in the absence of obstructions caused by the presence of an object. Then, based on the received light when the object is in the room, the algorithm infers the shape of the object. In addition, the algorithm considers the reflected paths from surfaces in order to determine the object's estimated shape. We study five different scenarios characterized by different levels of complexity, room sizes and a range of reflection nodes. The algorithm is also tested in a real prototype where several experiments are carried out in two scenarios to demonstrate the capabilities of Li-Tect in two and three dimensional monitoring and shape detection cases. Finally, the results show that the shape and the detection of objects in the scenarios can be easily acquired with high accuracy, even if the number of transceivers is reduced.
AB - In this paper, we propose Li-Tect, an algorithm to detect the shape of an object located in an indoor environment using low cost optical elements through sensing the environment's light. The algorithm analyzes, relying on the predictability of optical propagation paths, how much light is expected to propagate in the absence of obstructions caused by the presence of an object. Then, based on the received light when the object is in the room, the algorithm infers the shape of the object. In addition, the algorithm considers the reflected paths from surfaces in order to determine the object's estimated shape. We study five different scenarios characterized by different levels of complexity, room sizes and a range of reflection nodes. The algorithm is also tested in a real prototype where several experiments are carried out in two scenarios to demonstrate the capabilities of Li-Tect in two and three dimensional monitoring and shape detection cases. Finally, the results show that the shape and the detection of objects in the scenarios can be easily acquired with high accuracy, even if the number of transceivers is reduced.
KW - Ray Tracing
KW - Monitoring
KW - Visible Light Sensors
KW - Shape Detection
KW - Visible Light Communications
U2 - 10.1109/JSEN.2018.2879398
DO - 10.1109/JSEN.2018.2879398
M3 - Article
VL - 19
SP - 940
EP - 949
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
SN - 1530-437X
IS - 3
ER -