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R&D Technical Narrative: Software Example

R&D Example Technical Narrative


Work on this project commenced in [insert start date here] and was ongoing at the end of the reporting period.

What is the aim of this R&D project?

At the outset of this project, the primary objective was to develop a novel camera imaging and data analysis system and extend the capability of imaging tools in the industry as a whole.

What scientific or technological advance are you trying to achieve through this project?

The aim was to develop new technology that represents a significant advancement in the field of software development, as outlined in paragraph 9(c) of the BEIS guidelines.

Specifically, we aimed to create a robust, portable device which was capable of producing high quality images whilst preventing water ingress (IP55). The hardware needed to be integrated with proprietary backend architecture which could process data in an effective and low-latency manner.

The software component of the solution was multifaceted and involved the development of a proprietary image processing engine which could take disparate data and convert this into a format which could then be fed into an AI/ML system. The AI/ML system also needed to be built from scratch and integrated in a way which reduced latency and avoided any data loss.

In order to achieve this, we needed to build a prototype of the system equipped with a number of sensors, integrated software with cloud connectivity and additional characteristics such as a rechargeable power pack and a waterproof shell.

Our backend architecture was developed using the following technology [insert tech stack].

Provide a review of the current state of technology in the industry relating to the product or process you’re trying to build through this R&D project.

Current technology in the industry for this product/process is fragmented, with no solutions available that fully integrate all three components that we sought to offer.

One of our closest competitors produce similar technology, however, this requires the use of 3 separate, unintegrated systems. This results in a process which is less joined up and subsequently slower. We wanted to ensure that our system was fully integrated and responsive, without impacting image quality.

Another competitor makes similar hardware, however, this is not sufficiently robust for our proposed use. We initially tested their hardware for our solution, however during abuse and load testing it was discovered that the solution would not be fit for purpose.

Describe the unique methods and processes involved in your R&D project. How were they different from what is done in your industry

Typically, the approach in our industry is to utilise multiple unconnected systems to produce the desired result. Our approach was to integrate the three multiple systems into one, portable, robust solution with a back end which was fast, efficient and scalable.

We engaged in an iterative process of review and trailing of existing products and integrations and when our competent professionals discovered that existing technology was not fit for purpose, a period of prototyping and development commenced. This was achieved through physical prototyping and the development of custom tooling for the hardware element of the build, and the use of AGILE scrum and other techniques to develop our proprietary software architecture.

What scientific or technological uncertainties did you face?

At the beginning of the project, there existed technical uncertainties, the solution to which was not readily deducible to the competent professionals. These included:

  • System uncertainty: The competent professionals were uncertain whether the three components could be integrated into one functional and scalable system.
  • Scalability: We were uncertain whether our proposed development could handle large volumes of disparate data in a way which was effective, prevented data loss and most critically, was scalable.

Describe the issues the competent professionals encountered, and why they were not easily solvable

  • System uncertainty: The knowledge and capability on how to develop an entire system, integrating three separate technologies [list each technology here] is not available in the market and our competent professionals had to engage in an iterative period of testing and development to achieve a workable solution. [additional details on why each element of the integration provided a unique challenge should be given here]
  • Scalability: Developing a first in class prototype posed significant challenges during the iterative development process, including system uncertainties and integrating three disparate technologies into one solution. The competent professionals encountered further uncertainty as to whether the prototype was scalable because nothing like this had been developed before. The prototyping process demonstrated physical weaknesses with the product in addition to software vulnerabilities and data loss – the question asked was whether it would be possible to develop an integrated, workable solution at scale, without these issues arising.

Resolution of Technical Uncertainties

  1. Scalability: To resolve uncertainty around the scalability of our system, our competent professionals had to design and implement a [specific software] infrastructure cluster that could host all of our services which prevented data loss and kept latency low. At the end of the financial period, there still existed latency at an unacceptable level and work continues to resolve this. the competent professionals also tested a suite of existing software for high-frequency data capture, but nothing existed which provided the requisite performance. The competent professionals therefore worked to develop a proprietary solution, for which a fully-fledged product has not yet been completed. The physical design of the product including the housing, battery and mounting had to be designed from scratch, however it was discovered during the process that the housing was not sufficiently robust and the electroconductivity of the materials used were interfering with the operation of the device.
  2. We had to develop APIs and integration software to enable seamless communication between all three elements of the system, including bespoke sensors. We also had to ensure that our system could handle different types of data and formats, which required us to develop SQL schema validation and model checking to ensure data integrity and consistency.
  3. During an early iteration of the project, we attempted to utilise off-the-shelf sensors and software for data capture and transmission. However, we encountered significant technical difficulties in integrating these disparate systems and ensuring data consistency and integrity. Therefore, we had to develop a custom sensor and AI driver board for high-fidelity high-field-of-view image capture in the field, the knowledge of which was not publicly available.