The concentration in the new era of healthcare is medical Internet of things according to preventive and prediction (p2Health). In large scale and general perspective, the effective parameters from behavioral, ambient, and physiological domains as the most influencing fields of interest in healthcare, must be monitored. In personalized healthcare monitoring, wearables are playing an important role in terms of data measurement and collection. We aim at creating a configurable and adaptable platform for comprehensive parameters monitoring, according to convenient mode of wearability. Hence, we develop an innovative wrist-worn prototype for ambient monitoring, and a flexible IoT-gateway. The prototype measures the most critical parameters from ambient domain. In this platform, via IoT-gateway as an intermediate hub between wearables and IoT-server, bidirectional communication between the end-user and medics is established in real-time. In addition, physician as the real-time observer of patients are given the possibility to set up the required parameters for measurement through the IoT-gateway and activate/deactivate the sensors on the wearables. Therefore, depending on the target investigation, status of patients, requirements, and demands, medics can determine the setup parameters for measurement. Thus, the application of this platform is not limited to specific groups, but widely may be applied whether in daily routine or medical research investigation. Under the flexible IoT-gateway, the new wearables can readily be integrated and synchronized into the platform. The users are not restricted to select only one specific product but there are alternatives as well. To support the solution, experimental results are provided.

Recently, with the in-depth development of Industry 4.0 worldwide, mobile robots have become a research hotspot. Indoor localization has become a key component in many fields and the basis for all actions of mobile robots. This paper screened 147 papers in the field of indoor positioning of mobile robots from 2019 to 2021. First, 12 mainstream indoor positioning methods and related positioning technologies for mobile robots are introduced and compared in detail. Then, the selected papers were summarized. The common attributes and laws were discovered. The development trend of indoor positioning of mobile robots is obtained.

Currently, the process of tracking moving objects and determining their indoor location is considered to be one of the most attractive applications that have begun to see widespread use, especially after the adoption of this technology in some smartphone applications. The great developments in electronics and communications systems have provided the basis for tracking and location systems inside buildings, so-called indoor positioning systems (IPSs). The ultra-wideband (UWB) technology is one of the important emerging solutions for IPSs. This radio communications technology provides important characteristics that distinguish it from other solutions, such as secure and robust communications, wide bandwidth, high data rate, and low transmission power. In this paper, we review the implementation of the most important real-time indoor positioning and tracking systems that use ultra-wideband technology for tracking and localizing moving objects. This paper reviews the newest in-market UWB modules and solutions, discussing several types of algorithms that are used by the real-time UWB-based systems to determine the location with high accuracy, along with a detailed comparison that saves the reader a lot of time and effort in choosing the appropriate UWB-module/method/algorithm for real-time implementation.

Visual SLAM (Simultaneously Localization and Mapping) is a solution to achieve localization and mapping of robots simultaneously. Significant achievements have been made during the past decades, geography-based methods are becoming more and more successful in dealing with static environments. However, they still cannot handle a challenging environment. With the great achievements of deep learning methods in the field of computer vision, there is a trend of applying deep learning methods to visual SLAM. In this paper, the latest research progress of deep learning applied to the field of visual SLAM is reviewed. The outstanding research results of deep learning visual odometry and deep learning loop closure detect are summarized. Finally, future development directions of visual SLAM based on deep learning is prospected.

The leakage of hazardous gases and chemical vapors is considered one of the dangerous accidents that can occur in laboratories, workshops, warehouses, and industrial sites that use or store these substances. The early detection and alarming of hazardous gases and volatile chemicals are significant to keep the safety conditions for the people and life forms who are work in and live around these places. In this paper, we investigate the available mobile detection and alarming systems for toxic, hazardous gases and volatile chemicals, especially in the laboratory environment. We included papers from January 2010 to August 2021 which may have the newest used sensors technologies and system components. We identified (236) papers from Clarivate Web of Science (WoS), IEEE, ACM Library, Scopus, and PubMed. Paper selection has been done based on a fast screening of the title and abstract, then a full-text reading was applied to filter the selected papers that resulted in (42) eligible papers. The main goal of this work is to discuss the available mobile hazardous gas detection and alarming systems based on several technical details such as the used gas detection technology (simple element, integrated, smart, etc.), sensor manufacturing technology (catalytic bead, MEMS, MOX, etc.) the sensor specifications (warm-up time, lifetime, response time, precision, etc.), processor type (microprocessor, microcontroller, PLC, etc.), and type of the used communication technology (Bluetooth/BLE, Wi-Fi/RF, ZigBee/XBee, LoRa, etc.). In this review, attention will be focused on the improvement of the detection and alarming system of hazardous gases with the latest invention in sensors, processors, communication, and battery technologies.

The continued growth in life sciences is being accompanied by the constantly rising demand for robotic systems. Today, bioscreening and high–throughput screening processes are well automated. In contrast, a deficit can be found in the area of analytical measurements with complex and frequently changing processes. Robots undertake not only transportation tasks, but also direct sample manipulation and subsequent analytical measurements. Due to their human-like structure, dual-arm robots perform such processes similar to human operation. Liquid handling is required to transfer chemicals, to prepare standard solutions, or to dilute samples. Two electronic pipettes with different volume ranges (5–200 µL and 50–1000 µL) were integrated into a dual–arm robotic system. The main focus in this publication is the software interface for alternating robot and pipette control as well as the high–level process control system. The performance using a dual–arm robot equipped with electronic pipettes and conventional manual pipettes was determined and compared. The automation system presented is the first integration of a dual-arm robot in analytical measurement processes. Conventional manual laboratory pipettes and electronic pipettes are simultaneously used for liquid-handling tasks. The software control system enables a flexible and user-friendly process generation.