A low-cost indoor localization system based on received signal strength indicator by modifying trilateration for harsh environments

Received Signal Strength Indicator - Based Adaptive Localization Algorithm for Indoor Wireless Sensor Networks

Solutions for indoor localization have become more critical with recent advancement in context and location-aware technologies. When wireless sensor network (WSN) used in complex indoor environment, great propagation loss will be caused and it is very difficult to estimate adaptively the location of target nodes when environment changed. In this paper, an indoor adaptive localization algorithm ...

Learning Indoor Localization using Radio Received Signal Strength

A Robust Received Signal Strength Based Positioning Algorithm for Indoor Environments

Localization for mobile wireless sensor networks has been intensively studied in recent years due to its many applications in mobile networking as well as various public safety problems. However, the complexity of indoor radio propagation, especially when considering mobile users, makes indoor positioning a challenging task. This is mainly due to the severe multipath phenomenon where multiple c...

Received Signal Strength Indicator Node Localization Algorithm Based on Constraint Particle Swarm Optimization

Because the received signal strength indicator (RSSI) value greatly changes, the direct use of RSSI value has more errors in the positioning process as the basis to calculate the position of anchor nodes. This paper proposes a RSSI node localization algorithm based on constraint particle swarm optimization (PSO-RSSI). In the algorithm, particle swarm optimization is used to select anchor nodes ...

Comparative evaluation of Received Signal-Strength Index (RSSI) based indoor localization techniques for construction jobsites

This paper evaluates the accuracy of several RSSI-based localization techniques on a live jobsite and compares them to results obtained in an operating building. RSSI-based localization algorithms were tested due to their relative low cost and potential for accuracy. Four different localization algorithms (MinMax, Maximum Likelihood, Ring Overlapping Circle RSSI and k-Nearest Neighbor) were eva...