Ambient Monitoring Portable Sensor Node for Robot-Based Applications.

The leakage of gases and chemical vapors is a common accident in laboratory processes that requires a rapid response to avoid harmful effects if humans and instruments are exposed to this leakage. In this paper, the performance of a portable sensor node designed for integration with mobile and stationary robots used to transport chemical samples in automated laboratories was tested and evaluated. The sensor node has four main layers for executing several functions, such as power management, control and data preprocessing, sensing gases and environmental parameters, and communication and data transmission. The responses of three metal oxide semiconductor sensors, BME680, ENS160, and SGP41, integrated into the sensing layer have been recorded for various volumes of selected chemicals and volatile organic compounds, including ammonia, pentane, tetrahydrofuran, butanol, phenol, xylene, benzene, ethanol, methanol, acetone, toluene, and isopropanol. For mobile applications, the sensor node was attached to a sample holder on a mobile robot (ASTI ProBOT L). In addition, the sensor nodes were positioned close to automation systems, including stationary robots. The experimental results revealed that the tested sensors have a different response to the tested volumes and can be used efficiently for hazardous gas leakage detection and monitoring.

Evaluating of IAQ-Index and TVOC Parameter-Based Sensors for Hazardous Gases Detection and Alarming Systems.

The measurement of air quality parameters for indoor environments is of increasing importance to provide sufficient safety conditions for workers, especially in places including dangerous chemicals and materials such as laboratories, factories, and industrial locations. Indoor air quality index (IAQ-index) and total volatile organic Compounds (TVOC) are two important parameters to measure air impurities or air pollution. Both parameters are widely used in gases sensing applications. In this paper, the IAQ-index and TVOCs have been investigated to identify the best and most flexible solution for air quality threshold selection of hazardous/toxic gases detection and alarming systems. The TVOCs from the SGP30 gas sensor and the IAQ-index from the SGP40 gas sensor were tested with 12 different organic solvents. The two gas sensors are combined with an IoT-based microcontroller for data acquisition and data transfer to an IoT-cloud for further processing, storing, and monitoring purposes. Extensive tests of both sensors were carried out to determine the minimum detectable volume depending on the distance between the sensor node and the leakage source. The test scenarios included static tests in a classical chemical hood, as well as tests with a mobile robot in an automated sample preparation laboratory with different positions.

Evaluating a Novel Gas Sensor for Ambient Monitoring in Automated Life Science Laboratories.

Air pollution and leakages of hazardous and toxic gases and chemicals are among the dangers that frequently occur at automated chemical and life science laboratories. This type of accident needs to be processed as soon as possible to avoid the harmful side effects that can happen when a human is exposed. Nitrogen oxides and volatile organic compounds are among the most prominent indoor air pollutants, which greatly affect the lifestyles in these places. In this study, a commercial MOX gas sensor, SGP41, was embedded in an IoT environmental sensor node for hazardous gas detection and alarm. The sensor can detect several parameters, including nitrogen oxide index (NOx-Index) and volatile organic compound index (VOC-Index). Several tests were conducted to detect the leakage of nitrogen oxides and volatile organic compounds in different concentrations and volumes, as well as from different leakage distances, to measure the effect of these factors on the response speed and recovery time of the sensors used. These factors were also compared between the different sensors built into the sensor node to give a comprehensive picture of the system used. The system testing results revealed that the SGP41 sensor is capable of implementing the design purposes for the target parameters, can detect a small NO2 gas leakage starting from 0.3% volume, and can detect all the tested VOC solvents ≥ 100 µL.

Mobile Detection and Alarming Systems for Hazardous Gases and Volatile Chemicals in Laboratories and Industrial Locations.

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.

Flexible IoT Gas Sensor Node for Automated Life Science Environments Using Stationary and Mobile Robots.

In recent years the degree of automation in life science laboratories increased considerably by introducing stationary and mobile robots. This trend requires intensified considerations of the occupational safety for cooperating humans, since the robots operate with low volatile compounds that partially emit hazardous vapors, which especially do arise if accidents or leakages occur. For the fast detection of such or similar situations a modular IoT-sensor node was developed. The sensor node consists of four hardware layers, which can be configured individually regarding basic functionality and measured parameters for varying application focuses. In this paper the sensor node is equipped with two gas sensors (BME688, SGP30) for a continuous TVOC measurement. In investigations under controlled laboratory conditions the general sensors' behavior regarding different VOCs and varying installation conditions are performed. In practical investigations the sensor node's integration into simple laboratory applications using stationary and mobile robots is shown and examined. The investigation results show that the selected sensors are suitable for the early detection of solvent vapors in life science laboratories. The sensor response and thus the system's applicability depends on the used compounds, the distance between sensor node and vapor source as well as the speed of the automation systems.

An Optical Approach for Cell Pellet Detection.

Cell-based screening methods are increasingly used in diagnostics and drug development. As a result, various research groups from around the world have been working on this topic to develop methods and algorithms that increase the degree of automation of various measurement techniques. The field of computer vision is becoming increasingly important and has therefore a significant influence on the development of various processes in modern laboratories. In this work we describe an approach for detecting two height information, the phase boundary of a cell pellet and the bottom edge of the tube, and thereby a method for determining the highest point of the topology. The starting point for the development of the method described are cells obtained by various procedures and stabilized by a fixative. Centrifugation of the tube causes the cells to settle to the bottom of the tube, resulting in a cell pellet with a clear phase boundary between the cells and the fixative. For further studies, the supernatant fixative has to be removed without reducing the number of cells. The fixative is to be extracted automatically by a liquid robot, which is only possible by accurately determining the cell pellet height. Due to centrifugation, an uneven topology is formed, which is why the entire phase boundary must be examined to detect the highest point of the cell pellet. For this approach, the tube to be examined, which contains the cells and the fixative, is rotated 360° in defined small steps after centrifugation. During rotation, an image is captured in each step, after which a defined image area is separated from the center of the image and merged into a panoramic image. This produces a panoramic image of the cell topology which represents the complete phase boundary, the boundary located on the outside of the tube. This panoramic image is modified through various image processing steps to extract and detect the phase boundary. Various image processing algorithms from the OpenCV library are used. In the first step, the panoramic image is convolved with a Gaussian blur filter to reduce noise. In the following step, a black and white image is generated by a thresholding process. This black and white image, or binary image, is convolved with a Sobel operator in the x and y directions and the results are superimposed. This overlaid image shows the top edge of the cell pellet and other edges located in the image. A logical exclusion method of the obtained boundaries is used for the detection of the phase boundary. To detect the tube bottom, a multilevel model was trained in advance with an appropriate data set. This model can detect and localize in near real time the tube bottom in an image. By using the two-height information of the different boundaries, phase boundary and tube bottom, the highest point of the cell pellet can be detected. This information is then passed on to a higher-level process so that the liquid robot can approach this point with the pipette tip to remove the excess fixative. By determining the highest point, the probability of being able to remove a larger amount of fixative without reducing the number of cells is highest. This ensures that post-processing studies have the largest possible number of cells available with complete automation.

Automation in arthrosis research.

Widespread medical studies require the analysis of suitable sample numbers to discover certain effects. Arthrosis treatment with hip and knee joint endoprostheses introduces multiple materials into the human body. Metal-containing implants may release several degradation products. Certain concentrations of chromium, cobalt, nickel, titanium and aluminum may affect multiple organs. The determination of metal concentrations in body fluids is one way to prevent severe intoxication from implants. In addition, the study of metal distribution and accumulation in individual organs will deliver extended information. In contrast to well automated high-throughput screenings, analytical measurements are mostly performed manually due to their complex process structure. A new study published in the journal Molecules presents a semi-automated sample preparation and measurement system for the determination of metals in autopsy tissue using inductively coupled plasma mass spectrometry (ICP-MS). In this auto-commentary, the main findings are highlighted and discussed.

Integrating Mobile Robots into Automated Laboratory Processes: A Suitable Workflow Management System.

The general trend of automation is currently increasing in life science laboratories. The samples to be examined show a high diversity in their structures and composition as well as the determination methods. Complex automation lines such as those used in classic industrial automation are not a suitable solution with respect to the required flexibility of the systems due to changing application requirements. Rather, full automation requires the connection of several different subsystems, including manual process steps by the laboratory staff. This requires suitable workflow management systems that enable the planning and execution of complex process steps. The integration of mobile robots for transportation tasks is currently an important development trend for realizing full automation in life science laboratories. The article "Workflow Management System for the Integration of Mobile Robots in Future Labs of Life Sciences" presents the development and application of a hierarchical workflow management system (HWMS) as a top-level process management and control system. This concept combines the typical hierarchical automation structure with novel approaches for the integration of transportation tasks with variable degrees of automation. The aim is to create a general-purpose workflow management system that can be used in different areas of the life sciences, regardless of the specific device components and applications used.

Automated Analytical Measurement Processes Using a Dual-Arm Robotic System.

The demand for automation in the analytical laboratory is high. In contrast to well-automated bioscreening and high-throughput and high-content screening processes, analytical measurement procedures are complex in their structure and changing frequently. Not only do robotic units have to perform transportation or specific single tasks, but also flexible robots are needed to cover several tasks, including transportation and direct sample manipulation. Due to their human-like structure, dual-arm robots are predestined for analytical measurement processes. A new study published in the journal Energies presents a novel integration of electronic piston pipettes into an automation system using a dual-arm robot to perform liquid handling tasks similar to human operators. In this commentary, the main findings are highlighted and discussed.

Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources.

Investigations in preventive and occupational medicine are often based on the acquisition of data in the customer's daily routine. This requires convenient measurement solutions including physiological, psychological, physical, and sometimes emotional parameters. In this paper, the introduction of a decentralized multi-sensor-fusion approach for a preventive health-management system is described. The aim is the provision of a flexible mobile data-collection platform, which can be used in many different health-care related applications. Different heterogeneous data sources can be integrated and measured data are prepared and transferred to a superordinated data-science-oriented cloud-solution. The presented novel approach focuses on the integration and fusion of different mobile data sources on a mobile data collection system (mDCS). This includes directly coupled wireless sensor devices, indirectly coupled devices offering the datasets via vendor-specific cloud solutions (as e.g., Fitbit, San Francisco, USA and Nokia, Espoo, Finland) and questionnaires to acquire subjective and objective parameters. The mDCS functions as a user-specific interface adapter and data concentrator decentralized from a data-science-oriented processing cloud. A low-level data fusion in the mDCS includes the synchronization of the data sources, the individual selection of required data sets and the execution of pre-processing procedures. Thus, the mDCS increases the availability of the processing cloud and in consequence also of the higher level data-fusion procedures. The developed system can be easily adapted to changing health-care applications by using different sensor combinations. The complex processing for data analysis can be supported and intervention measures can be provided.

Flexible Automation System for Determination of Elemental Composition of Incrustations in Clogged Biliary Endoprostheses Using ICP-MS.

Automation systems are well established in industries and life science laboratories, especially in bioscreening and high-throughput applications. An increasing demand of automation solutions can be seen in the field of analytical measurement in chemical synthesis, quality control, and medical and pharmaceutical fields, as well as research and development. In this study, an automation solution was developed and optimized for the investigation of new biliary endoprostheses (stents), which should reduce clogging after implantation in the human body. The material inside the stents (incrustations) has to be controlled regularly and under identical conditions. The elemental composition is one criterion to be monitored in stent development. The manual procedure was transferred to an automated process including sample preparation, elemental analysis using inductively coupled plasma mass spectrometry (ICP-MS), and data evaluation. Due to safety issues, microwave-assisted acid digestion was executed outside of the automation system. The performance of the automated process was determined and validated. The measurement results and the processing times were compared for both the manual and the automated procedure. Finally, real samples of stent incrustations and pig bile were analyzed using the automation system.