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In the Internet of Things (IoT) era with the wide employment of Mobile Devices (MDs), the distribution of video streams is continuously increasing and specific solutions for transmissions between mobiles are needed. In this paper, we provide the performance comparison, through emulations, among Application Layer Joint Coding approaches for videos over channels whose conditions change over time. The proposed analysis highlights that the video streaming over such critical channels is practicable, from the Quality of Experience (QoE) viewpoint, only if source and channel coding are both adaptively applied to the video transmissions.

Different positioning schemes are based on the probability p ( o | l ) to have an observation vector o at a Reference Point (RP) l , based on Gaussian probabilities. This paper presents an approach to speed-up the p ( o | l ) computation without any approximation. The consequent positioning scheme is called Smart P-FP. The comparison between Traditional (without any p ( o | l ) acceleration) and Smart P-FP is performed over different smartphones. The saved energy is about 90% for a large number of Access Points (APs) but is significant even with few APs: more than 86% with 3 APs. The proposed p ( o | l ) computation is beneficial to any p ( o | l ) -based positioning scheme.

The paper describes an original architecture aimed at tracking assets within construction sites. The main components are Radio Frequency IDentification (RFID), Bluetooth Low Energy (BLE) tags and smartphones. The core functions are performed by two Android applications, which implement asset tracking and searching. The main merits of the architecture are its ability to maximize smartphone battery lifetime, that can reach an entire working shift, very satisfactory accuracy of BLE tag-smartphone distance estimation (with a mean error around 2 m), high probability of detecting all the tags present in the construction site, as well as a suitably short Aging time.