RoC: Robust and Low-Complexity Wireless Indoor Positioning Systems for Multifloor Buildings Using Location Fingerprinting Techniques

Table 1

Recent system design approaches for indoor positioning systems.

Category	Scheme	Localization algorithm	Optimization method	Design objectives	Design limitations	Service areas	Robustness (support in RN-failure situation)
Triangulation	[10]	RSS-based	Tabu search	To minimize localization error	The design does not consider minimizing the number of RNs	Single floor	No
	[11]	Distance-based	Genetic Algorithm	To maximize signal coverage and minimize number of RNs	The selected fitness evaluation influences the localization results	Single floor	No
	[12]	TOA	—	To minimize localization error	The RN placement has only a uniform angular distribution	Single floor	No
Scene analysis	[13]	KNN	Simulated Annealing	To minimize total number of similar fingerprints	The dynamic nature of the indoor environment is not considered in the system design	Single floor	No
	[14]	WKNN	—	To maximize signal RSS and minimize noise	The design does not consider the signal coverage in the physical surroundings	Single floor	No
	[15]	KNN	Simulated Annealing	To maximize fingerprint difference	Complicated indoor layouts influence the minimum number of RNs	Single floor	No
	[16]	Euclidean distance	Simulated Annealing	To maximize summation of maximum RSS	The RN placement design lacks system reliability	Single-floor and multifloor	No
	Proposed design	Active Fusion	Simulated Annealing	To minimize number of RNs and find their optimum locations to be provisioned to support RN-failure situations	The design considers only the discrete candidate sites for installing RNs	Single floor and multifloor	Yes