Cadastral reinstatement methods within Queensland involve the use of modern digital surveying techniques in combination with traditional non-digital methods of recording and reporting information. This leads to the need to manually enter and re-enter data into a digital format at different stages of a survey. The requirement to lodge survey information with government organisations in a non-digital survey plan format also forces a break in digital data flow throughout the cadastral surveying system, which can only be updated by changes in the lodgement regulations. The private cadastral organisations are predominantly responsible for carrying out the cadastral surveys and the government agencies are primarily responsible for the examination, verification and administration of the cadastral data. These organisations will have no communication link for digital cadastral data until the introduction of digital data lodgement. The digital system within the private cadastral surveying organisations can therefore be considered to be an independent system with consideration needed to be given to the future introduction of a digital lodgement system at some undefined time in the future. Cadastral surveyors hold large amounts of digital information that is suitable for digital reinstatement systems. This information, if appropriately archived and distributed, has the capacity to meet the needs of reinstatement systems including as an alternative source of digital information that will eventually be obtained from digital lodgement systems. The existing technology and the private organisation structures are capable of supporting continuous digital data flow and automated systems. This research proposes a process of development for private cadastral organisations to advance from traditional systems to continuous digital data flow and automated processes within their cadastral reinstatement systems. The development process is linked to existing legislation and technology taking into consideration likely future directions. The current legislative and technological environments within Queensland allow for development towards automated digital systems that will enhance most current cadastral reinstatement systems.

As small-form factor drones grow more intelligent, they increasingly require more sophisticated capabilities to record sensor data and system state, ensuring safe and improved operation. Already regulations for black boxes, electronic data recorders (EDRs), for determining liabilities and improving the safety of large-form factor autonomous vehicles are becoming established. Conventional techniques use hardened memory storage units that conserve all sensor (visual) and system operational state; and N-way redundant models for detecting uncertainty in system operation. For small-form factor drones, which are highly limited by weight, power, and computational resources, these techniques become increasingly prohibitive. In this paper, we propose a safety architecture for resource constrained autonomous vehicles that enables the development of safer and more efficient nano-drone systems. The insight for the proposed safety architecture is that the regular structure of data-driven models used to control drones can be exploited to efficiently compress and identify key events that should be conserved in the EDR subsystem. We describe an implementation of the architecture, including hardware and software support, and quantify the benefits of the approach. We show that the proposed techniques can increase the amount of recorded flight time by over 10x and reduce energy usage by over 10x for high-resolution systems.