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Nowadays, indoor localisation is among the most important challenges in IoT networks. Furthermore, deep learning techniques are emerging as a leading method. Additionally, meta-heuristic algorithms attract several research domains due to its efficiency ...

With rising demand for indoor location-based services (LBS) such as location-based marketing, mobile navigation, etc., there has been considerable interest in indoor positioning methods as well as their security and privacy. Current ...

Positioning is an enabler for many location-based services in the vertical industrial domain such as autonomous driving and robot-to-cobot interaction, to name a few. Industry and academia are actively enabling localization through 5G and WiFi as they ...

Artificial intelligence is getting a foothold in medicine for disease screening and diagnosis. While typical machine learning methods require large labeled datasets for training and validation, their application is limited in clinical ...

• Application of unsupervised learning for automated clustering of spectra profiles.

• Two Time-of-Flight technologies have been tested to develop a yield monitor.
• Two algorithms have been developed for weight estimation by volume measurement.
• Some factors such as illumination or acceleration affect the accuracy.

The introduction of fruit tree harvesters on the market allows the opportunity to incorporate new yield monitors. Traditionally, yield has been measured by in-the-field fruit batch weighing systems that employ load cells, which present certain ...

Millimeter-wave (mmWave) technology is an important element to increase the throughput and reduce latency of future wireless networks. At the same time, its high bandwidth and highly directional antennas allow for unprecedented accuracy in wireless ...

To solve the problem that single natural scene image acquisition information in an orchard cannot meet the requirements of accurate fruit recognition and target positioning, a new apple image fusion algorithm based on the binocular acquisition system ...

• The introduction of new sensors and AI methodologies have increased detection performance.

In the last few years, the use of artificial intelligence and technological advances such as deep learning, new 3D-capable sensors, and edge computing embedded systems have increased produce detection and localization performance for ...

WiFi location systems are remarkably accurate, with decimeter-level errors for recent CSI-based systems. However, such high accuracy is achieved under Line-of-Sight (LOS) conditions and with an access point (AP) density that is much higher than that ...

3D vision technique can digitize the real world and build an accurate 3D digital environment, which is considered as one of the standard technologies for the next generation of mobile smart products. Limited by the hardware, the dynamic 3D imaging ...

Recently a wide variety of applications has been developed integrating 3D functionalities. Advantages given by the possibility of relying on depth information allows the developers to design new algorithms and to improve the existing ones. In ...

Recently wireless sensor network (WSN) applications have been in high demand. The key aspects of these applications is 'localisation'. Due to low energy and limited processing capability, many sensor nodes do not have any knowledge about their location, ...

This paper proposes a method for fusing data acquired by a ToF camera and a stereo pair based on a model for depth measurement by ToF cameras which accounts also for depth discontinuity artifacts due to the mixed pixel effect. Such model is exploited ...

Modern car wash systems are generally controlled by light barriers and power measurement sensors. These sensors are directly mounted on the movable parts of the system which result in a slow regulation, leading to non-optimal performance, e.g. in terms ...