Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization.

With evolution of the smart things, to acquire data, gateways play a major role in interconnecting with various sensor nodes. Using different wireless protocols and standards with sensor nodes, gateway can transform information into a unique format that transmits into the cloud for further use. Which accepts the commands from external users in the remote location through a personal computer or a smartphone? The proposed gateway has its added advantages; (i) ZigBee and Wi-Fi wireless technologies connectivity is enabled, (ii) transforms the information into required protocol format, (iii) uses a light weighted MQTT protocol in transmitting and receiving environment, (iv) It provides the storage and analyzed data and (v) the sensor values can be observed and the devices can be controlled by a smartphone from remote location. Here we demonstrate the proof of concept for controlling the smart home appliances. This also represents a design and implementation of Bi-Directional IoT gateway using ZigBee and Wi-Fi technologies with MQTT protocol.

In smart home, location estimation based on PIR sensors is very popular. Existing methods by various sensors technologies and intelligent algorithms are used to achieve a high accuracy. In fact, how to deploy the PIR sensor is directly related to the accuracy. In this paper, we present an approach to deploying the PIR sensor based on the accessible priority by genetic algorithm. This paper presents a genetic algorithm that searches for an optimal or near optimal solution to the PIR sensor deployment for smart home. The fitness function of GA is based on the accessible priority of indoor areas. The accessible priority value of different area is set according to the indoor environment and daily accessible habits. The performance of the genetic algorithm was evaluated using several metrics, and the simulation results demonstrated that the proposed algorithm can optimize the network coverage in terms of accessible frequency.