The Machine that Lives Forever
type: CreativeWork
description: Design an intelligent micromachine that can self-power and sustain from environmental energy scavenging to achieve an autonomous device that can communicate at will with peers indefinitely. Explore sleep/wake hibernation strategies coupled with food scavenging off-grid traits to identify the tightest work to sleep efficiency schedule, incorporating adaptive reconfiguration to manage significant environmental impacts. Capture, store and manage background radiations and stray RF signals to feed on in a continued effort to make intelligent survival decisions and oversee management protocols. Ensure that every micro Watt of usable energy gets extracted from every part of the harvest and then forward-scheduled it for productive use. Finally, employ natures tricks and experience to introduce essential personality traits, pursuing maximising survival numbers and increasing dispersal target area sizes of large self-sufficient wireless sensor deployments. This research intends to provide a closely coupled software-hardware foundation that aids implementers in intelligently harnessing and using tiny amounts of ambient energy in a highly autonomous way. This platform then continues on to explore ways of maximising the efficient usage of the harvested energy using various hibernation/wake strategies and then making objective comparisons with proposed intelligent energy management protocols. Finally, the protocol extends to enable the device to manage its personal survival possibilities so the devices can use an evolutional personality-based approach to deal with the unknown environmental situations they will encounter. This work examines a machine that can self-power and sustain from environmental energy scavenging with the aim to live forever. Living forever implies a brain (microcontroller) that can manage energy and budget for continuous faculty. With these objectives, sleep/wake/hibernation and scavenging strategies are examined to efficiently schedule resources within a tr…
abstract: Design an intelligent micromachine that can self-power and sustain from environmental energy scavenging to achieve an autonomous device that can communicate at will with peers indefinitely. Explore sleep/wake hibernation strategies coupled with food scavenging off-grid traits to identify the tightest work to sleep efficiency schedule, incorporating adaptive reconfiguration to manage significant environmental impacts. Capture, store and manage background radiations and stray RF signals to feed on in a continued effort to make intelligent survival decisions and oversee management protocols. Ensure that every micro Watt of usable energy gets extracted from every part of the harvest and then forward-scheduled it for productive use. Finally, employ natures tricks and experience to introduce essential personality traits, pursuing maximising survival numbers and increasing dispersal target area sizes of large self-sufficient wireless sensor deployments. This research intends to provide a closely coupled software-hardware foundation that aids implementers in intelligently harnessing and using tiny amounts of ambient energy in a highly autonomous way. This platform then continues on to explore ways of maximising the efficient usage of the harvested energy using various hibernation/wake strategies and then making objective comparisons with proposed intelligent energy management protocols. Finally, the protocol extends to enable the device to manage its personal survival possibilities so the devices can use an evolutional personality-based approach to deal with the unknown environmental situations they will encounter. This work examines a machine that can self-power and sustain from environmental energy scavenging with the aim to live forever. Living forever implies a brain (microcontroller) that can manage energy and budget for continuous faculty. With these objectives, sleep/wake/hibernation and scavenging strategies are examined to efficiently schedule resources within a tr…
author: Walton, Michael
language: en
keywords: T Technology (General), TK Electrical engineering. Electronics Nuclear engineering
date published: 2021-07
date modified: 2026-07-24T02:18:43Z
provider: University of Essex
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Essex