Universal Robotic Platform for Diagnosis and Spot Spraying of Trees and Shrubs

The number of threats to the plants is constantly increasing. The harmful impact of pests and plant diseases costs billions of dollars to the global economics each year. Chemical protection of plants from diseases and insects became an urgent problem in crop production, forestry and parks. The study aimed to develop an effective mobile robot for treating trees and shrubs from insects and diseases by spraying with chemicals. The work used monographic and general scientific research methods. A review of existing designs and technologies, as well as an analysis of publications in leading scientific journals, led to the conclusion that there is no one generally accepted technology for remote diagnosis and spot spraying of single trees and shrubs. Most of the technical means used have significant technical and environmental limitations. Currently, there is no unambiguous decision about which machine and technology to choose for solving the problems of remote diagnostics and spot spraying of single plant objects with a height of 2 to 4 meters. Taking into account the identified requirements, a robotic platform was developed for diagnosing and spot spraying of ornamental and fruit trees and tall shrubs. The developed robot is equipped with the necessary set of equipment for moving around the territory and spraying objects, has an increased cross-country ability, works according to a given program, has a minimal environmental impact, and can record data for diagnosing problems on plants. The proposed universal robot can work in agricultural, forest and urban areas, in warehouses and production facilities.

Residual life management of cyber-physical transport systems

The article deals with the problem of assessing the residual life of robotic agricultural vehicles. This problem is inextricably linked to the organization of effective vehicle maintenance. The robotic vehicle has a multifunctional remote diagnostics system, which makes it possible to assess the probability of component failure in real-time. In virtual commissioning, simulation is the most appropriate tool for researching and finding effective maintenance solutions. A simulation model based on timed colored Petri nets is proposed. The structure of the model is given, and its modules are described. Research is carried out by the method of statistical tests on a simulation model. An example of evaluating the delays in executing a production task, depending on the maintenance procedures and the probabilities of robotic vehicle unit failures, is given.

Vision Atrophy Screening and Revelation

Glaucoma which is known as the “thief of sight”, is an irreversible eye disease It is mainly caused by increased intraocular pressure (IOP), or loss of blood supply to the optic nerve. Glaucoma detection and diagnosis is very important. By analyzing the optic disc and its surroundings, This paper introduces a method for providing automated glaucoma screening services based on a framework that proposes a retinal image synthesizer for glaucoma assessment by analyzing the optic disc and its surroundings. The Cup to Disc Ratio (CDR) is critical for the system, and it is calculated using 2-D retinal fundus images. The synthetic images produced by our system are compared quantitatively. The structural properties of synthetic and real images are analyzed, and the quality of colour is calculated by extracting the 2-D histogram. The system allows patients to receive low-cost remote diagnostics from a distance, preventing blindness and vision loss by early detection and management.

Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation

The article describes a complex of non-contact methods for remote diagnosis of high-voltage insulators as well as the two-channel method for remote diagnostics of the operating state of high-voltage insulators, based on the registration of partial discharges by electromagnetic and acoustic sensors. The presented device allows visual inspection and searches for faulty high-voltage equipment and a remote non-contact method of recording high-intensity electric fields of industrial frequency and their spatial distribution based on the electro-optical effect. The scheme of using the system for monitoring and diagnosing the technical condition of high-voltage support insulators of open switchgear is described. The results of experimental studies confirm the possibility of industrial applicability of the proposed method for non-contact remote diagnostics of the state of high-voltage insulators under operating voltage.

Optimized workflow for digitalized FISH analysis in pathology

Background Effective workflow management in a diagnostic pathology laboratory is critical to achieve rapid turnover while maintaining high quality. Fluorescence in situ hybridization analysis (FISH) is the preferred technique for detecting single chromosomal aberrations in diagnostic surgical pathology. Material and methods FISH analysis applying a rapid hybridization protocol and using an automated whole-slide fluorescence scanning device (3DHISTECH, Sysmex, Switzerland) were implemented in our workflow. By analyzing 42 diagnostic cases, effects of two different scanning profiles on scanning time, and device memory usage were investigated. Manual signal counting (CaseViewer) and software based signal counting (FISHQuant) were compared. Results The two scanning profiles, both including a Z-stack function, differed in their exposure time and digital gain. The “low profile” setting (LP) resulted in a significantly shorter scanning time and lower storage volume compared to the “high profile” (HP) setting, making the LP ideal for routine applications. Both signal counting methods (manual versus software based) provided similar cut-offs on a test-cohort of 13 samples. Conclusion Scanning FISH slides provides good picture quality, reduces the analysis time and allows easy picture archiving and facilitates remote diagnostics, allowing an effective workflow.

A digital nervous system aiming toward personalized IoT healthcare

Body area networks (BANs), cloud computing, and machine learning are platforms that can potentially enable advanced healthcare outside the hospital. By applying distributed sensors and drug delivery devices on/in our body and connecting to such communication and decision-making technology, a system for remote diagnostics and therapy is achieved with additional autoregulation capabilities. Challenges with such autarchic on-body healthcare schemes relate to integrity and safety, and interfacing and transduction of electronic signals into biochemical signals, and vice versa. Here, we report a BAN, comprising flexible on-body organic bioelectronic sensors and actuators utilizing two parallel pathways for communication and decision-making. Data, recorded from strain sensors detecting body motion, are both securely transferred to the cloud for machine learning and improved decision-making, and sent through the body using a secure body-coupled communication protocol to auto-actuate delivery of neurotransmitters, all within seconds. We conclude that both highly stable and accurate sensing—from multiple sensors—are needed to enable robust decision making and limit the frequency of retraining. The holistic platform resembles the self-regulatory properties of the nervous system, i.e., the ability to sense, communicate, decide, and react accordingly, thus operating as a digital nervous system.

Understanding the role of digital platforms in technology readiness

State-of-the-art digital tools that take advantage of machine learning-derived algorithms and advanced data analytics have the potential to transform regenerative medicine by enabling investigators and clinicians to extract intelligence and actionable insights from published studies, electronic health records, pathology images and a variety of other sources. Used in isolation, however, these tools are not as effective as they can be integrated into a comprehensive strategy – a platform. We discuss the value of a platform strategy by summarizing several initiatives that have been launched at Mayo Clinic, including a clinical data analytics platform, a remote diagnostics and management platform and a virtual care system.