Steady-State Visual Evoked Potential (SSVEP) is a visual cortical response evoked by repetitive stimuli with a light source flickering at frequencies above 4 Hz and could be classified into three ranges: low (up to 12 Hz), medium (12-30) and high frequency (> 30 Hz). SSVEP-based Brain-Computer Interfaces (BCI) are principally focused on the low and medium range of frequencies whereas there are only a few projects in the high-frequency range. However, they only evaluate the performance of different methods to extract SSVEP.

This article presents a description of the design, development, and implementation of web-based software and dedicated hardware which allows for the remote monitoring and control of a drip irrigation system. The hardware consists of in-field stations which are strategically distributed in the field and equipped with different sensors and communication devices; a weather station and drip irrigation system complete the setup. The web-based software makes it possible to remotely access and process the information gathered by all the stations and the irrigation controller. The proposed system was implemented in a young olive orchard, located in the province of San Juan, an arid region of Argentina. The system was installed and evaluated during the seasons 2014–2015 and 2015–2016. Four regulated irrigation strategies were proposed in the olive orchard to test its behavior. In this pilot experiment, the precision irrigation system was a useful tool for precisely managing the irrigation process, applying only the required amount of water (precise irrigation). Regulated deficit irrigation experiments, on the other hand, have demonstrated the sensitivity of olives to water restriction. The precision irrigation system made it possible to control soil moisture levels, avoiding water stress in the control treatment.

In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work.

SUMMARY: This paper proposes a prediction system and a command fusion to help the human operator in a teleoperation system of a mobile robot with time-varying delay and force feedback. The command fusion is used to join a remote controller and the delayed user's commands. Besides, a predictor is proposed since the future trajectory of the mobile robot is not known a priori being it decided online by the user. The command fusion and predictor are designed based on the time delay and the current context measured through the crash probability. Finally, the proposed scheme is tested from teleoperation experiments considering time-varying delay as well as force feedback.