This work has an innovative approach for the development of nanorobots with sensors for medicine. The nanorobots operate in a virtual environment comparing random, thermal and chemical control techniques. The nanorobot architecture model has nanobioelectronics as the basis for manufacturing integrated system devices with embedded nanobiosensors and actuators, which facilitates its application for medical target identification and drug delivery. The nanorobot interaction with the described workspace shows how time actuation is improved based on sensor capabilities. Therefore, our work addresses the control and the architecture design for developing practical molecular machines. Advances in nanotechnology are enabling manufacturing nanosensors and actuators through nanobioelectronics and biologically inspired devices. Analysis of integrated system modeling is one important aspect for supporting nanotechnology in the fast development towards one of the most challenging new fields of science: molecular machines. The use of 3D simulation can provide interactive tools for addressing nanorobot choices on sensing, hardware architecture design, manufacturing approaches, and control methodology investigation.

This work presents a new approach with details on the integrated platform and hardware architecture for nanorobots application in epidemic control, which should enable real time in vivo prognosis of biohazard infection. The recent developments in the field of nanoelectronics, with transducers progressively shrinking down to smaller sizes through nanotechnology and carbon nanotubes, are expected to result in innovative biomedical instrumentation possibilities, with new therapies and efficient diagnosis methodologies. The use of integrated systems, smart biosensors, and programmable nanodevices are advancing nanoelectronics, enabling the progressive research and development of molecular machines. It should provide high precision pervasive biomedical monitoring with real time data transmission. The use of nanobioelectronics as embedded systems is the natural pathway towards manufacturing methodology to achieve nanorobot applications out of laboratories sooner as possible. To demonstrate the practical application of medical nanorobotics, a 3D simulation based on clinical data addresses how to integrate communication with nanorobots using RFID, mobile phones, and satellites, applied to long distance ubiquitous surveillance and health monitoring for troops in conflict zones. Therefore, the current model can also be used to prevent and save a population against the case of some targeted epidemic disease.

This work describes an innovative medical nanorobot architecture based on important discoveries in nanotechnology, integrated circuit patents, and some publications, directly or indirectly related to one of the most challenging new fields of science: molecular machines. Thus, the architecture described in this paper reflects, and is supported by, some remarkable recent achievements and patents in nanoelectronics, wireless communication and power transmission techniques, nanotubes, lithography, biomedical instrumentation, genetics, and photonics. We also describe how medicine can benefit from the joint development of nanodevices which are derived, and which integrate techniques, from artificial intelligence, nanotechnology, and embedded smart sensors. Teleoperated surgical procedures, early disease diagnosis, and pervasive patient monitoring are some possible applications of nanorobots, reflecting progress along a roadmap for the gradual and practical development of nanorobots. To illustrate the described nanorobot architecture, a computational 3D approach with the application of nanorobots for diabetes is simulated using clinical data. Theoretical and practical analysis of system integration modeling is one important aspect for supporting the rapid development in the emerging field of nanotechnology. This provides useful directions for further research and development of medical nanorobotics and suggests a time frame in which nanorobots may be expected to be available for common utilization in therapeutic and medical procedures.

The authors present a new approach using genetic algorithms, neural networks, and nanorobotics concepts applied to the problem of control design for nanoassembly automation and its application in medicine. As a practical approach to validate the proposed design, we have elaborated and simulated a virtual environment focused on control automation for nanorobotics teams that exhibit collective behavior. This collective behavior is a suitable way to perform a large range of tasks and positional assembly manipulation in a complex three-dimensional workspace. We emphasize the application of such techniques as a feasible approach for the investigation of nanorobotics system design in nanomedicine. Theoretical and practical analyses of control modeling is one important aspect that will enable rapid development in the emerging field of nanotechnology.

The author presents a new approach within advanced graphics simulations for the problem of nano-assembly automation and its application for medicine. The problem under study concentrates its main focus on nanorobot control design for assembly manipulation and the use of evolutionary competitive agents as a suitable way to warranty the robustness on the proposed model. Thereby the presented paper summarizes as well distinct aspects of some techniques required to achieve a successful nano-planning system design and its simulation visualization in real time