Providing IoT Services in Smart Cities through Dynamic Augmented Reality Markers

Abstract

Smart cities are expected to improve the quality of life of citizens by relying on new paradigms, such as the Internet of Things (IoT) and its capacity to manage and interconnect thousands of sensors and actuators scattered across the city. At the same time, mobile devices widely assist professional and personal everyday activities. A very good example of the potential of these devices for smart cities is their powerful support for intuitive service interfaces (such as those based on augmented reality (AR)) for non-expert users. In our work, we consider a scenario that combines IoT and AR within a smart city maintenance service to improve the accessibility of sensor and actuator devices in the field, where responsiveness is crucial. In it, depending on the location and needs of each service, data and commands will be transported by an urban communications network or consulted on the spot. Direct AR interaction with urban objects has already been described; it usually relies on 2D visual codes to deliver object identifiers (IDs) to the rendering device to identify object resources. These IDs allow information about the objects to be retrieved from a remote server. In this work, we present a novel solution that replaces static AR markers with dynamic markers based on LED communication, which can be decoded through cameras embedded in smartphones. These dynamic markers can directly deliver sensor information to the rendering device, on top of the object ID, without further network interaction.

User-Aware Audio Marker Using Low Frequency Ultrasonic Object Detection and Communication for Augmented Reality

“…However, the spectrogram without the person was quite similar to the background image, as noticed in Figure 5c. By subtracting Figure 5e from Figure 5c, the spectrogram image in Figure 5f became small, which resulted in a low a priori SNR, ξ(p, n), in Equation (12). In contrast, the reflected LFU remained significantly in the spectrogram image when the person was within 4 m, as shown in Figure 5h,i, before and after subtracting the background, respectively.…”

“…Next, b i is then encoded by an FEC algorithm [19]; thus, additional error correction bits are attached. In particular, a perfect binary Golay code, G 23 , is used for FEC encoding [19], i.e., b i is reshaped into an O × 12 matrix, and it is encoded by the (23,12) Golay block. Consequently, an O × 23 encoded block for the i-th symbol, b i , is generated.…”

“…While recent AR applications tried to recognize visual environments without using a marker, in order to deploy virtual objects in natural ways [9], such attempts required substantial computations of the AR device; thus, their use was limited to a certain AR scenario [10]. Visual marker limitations could also be avoided by using other marker types, such as gyroscope and global positioning system (GPS) sensors [11,12], but unfortunately, such markers were difficult to establish in indoor environments [11]. For example, while motion detection sensors, e.g., pyroelectric infrared (PIR) sensors, could work as indoor markers for some AR applications [13], PIR sensors failed to send rich information regarding virtual objects or events to the AR device.…”

Hybrid Solution Combining Kalman Filtering with Takagi–Sugeno Fuzzy Inference System for Online Car-Following Model Calibration

“…Currently, ITS development involves the usage of Bluetooth sensors in the TMS (traffic monitoring systems). This approach applied in several cities can enhance their chance to become smart cities and, implicitly, to improve the citizens’ quality of life [ 5 ]. This sensing technology proved its utility in travel times estimation and traffic signal control.…”

An Open Source Software Architecture for Smart Buildings

“…A localization approach was introduced as tracking systems based on CPS [34] to produce location-based services [48]: a database was built and Markov-chain prediction model was used to assist the positioning based on the stored data [26]. CPS is a component of the Building Management Systems (BMS) responsible could function as fault detection and diagnosis tool in the system [35], aiming to enhance maintenance services and reduce its cost [36].…”