"Industry 4.0 fosters what has been called a "smart factory". Within modular structured smart factories, cyber-physical systems monitor physical processes and make decentralized decisions. Industrial Internet of Things (IIoT) systems enable the connectivity of numerous heterogeneous devices and other assets into one system to derive more intelligent actions from data. The application of the IIoT in industrial production systems is known as Industry 4.0".(Wikipedia ABB_D_)

Industrial automation companies including ABB, Bosch, BMW and Audi envision that in these smart factories of the future people will control the operations and make decisions based on measurement data from the factory's equipment, as well as information regarding the availability of raw materials and the price of energy. This will improve productivity, in more environmentally friendly manner and reduce costs. (ABB).

Our product, Radiance-T will give manufacturers the ability to transition personnel to more value-added activities, providing the foundation to extend and expand product and service offerings. As they look to expand globally, our automated temperature and thermal image monitoring solution will maintain process consistency across locations. The information will be delivered to experts who are far away from the facility itself, for example in applications for the oil and gas industry or for offshore wind power plants. The product can pre-emptively detect and analyze faults and send reports to operation and production planning systems.

What it does

Our device provides clients with the ability to remotely access data from Radiance's on-board thermographic camera and thermopile sensors to enforce quality control standards of temperature-sensitive goods such as perishables or heat-sensitive chemicals during processing or manufacturing. It enables clients to monitor and perform operations effectively on assembly and manufacturing lines. It provides the visual sight on location where human inspection or visual camera monitoring are difficult.

Radiance's sensors are mounted on a 180-degree swivel platform powered by a remotely controlled servo motor, allowing the client to get temperature readings with a 235-degree field of view. All the logged data is easy accessible to clients via our cloud dashboard.

Clients can also update Radiance's firmware to take advantage of the latest features using the Over The Air Firmware Update capabilities accessible through our cloud application interface/dashboard. Increasing automation improves the quality of the entire value chain. The person can use information to program and control operations and make decisions to optimize the quality, safety, efficiency and environmental aspects of production.

Application Features

How we built it

  1. Product design phase with feature and sensor selection.
  2. Designing electrical schematics using Altium Designer to enable PCB design.
  3. Designing PCB, routing components, satisfying manufacturers Design Rule Checks.
  4. Exporting PCB design, submitting it to manufacturer and resolving any last-minute issues.
  5. Developing firmware for the PCB, including developing a CLI, Bootloader, and OTAFU functionality using the Atmel Studio IDE and ASF libraries for the SAMD21 MCU.
  6. Connecting the hardware to Node-Red using the MQTT broker.
  7. Designing UI Interface for Radiance using Node-Red IDE with simulation functionality.
  8. Perform board bring-up on our manufactured PCBs, and integrate sensors using I2C, Serial and ADC interfaces.

Challenges we ran into

Firmware Integration. Following the checkpoint structure of the course, we developed all the core firmware functionality such as CLI, boot loader, OTAFU and each sensor's interface in independent projects. In the last few weeks of the course when we tried to merge all the software projects to create a singular 2000+ line project, we ran into a lot of conflicts. Examples were using different timers, sensor modules using the same SERCOM pins, or condensing or trying to compress a polling-based while(true) loop using interrupt driven programming.

PCB Design. Our primary challenge in the second stage of our project was narrowing down the functionality and complexity of our board to fit under the $30 / board budget. Significant challenges we faced when tasked with designing the schematics and the board for our PCB, component selection based on size, availability and cost was major challenge. Moreover, complying with PCB manufacture's requirement was most important thing in this phase.

PCB Bring-up. Testing signal connectivity and voltage levels and making sure power blocks works as we designed them for.

Sensor Integration - Interfacing two different I2C sensors on the same I2C line with master processor and calibration of complex temperature sensor on the board.

Product Management- Cost and timeline were major challenges in the development life cycle

Accomplishments that we're proud of

  • Build a working prototype for Radiance -T which can be tested with conditions
  • Designed a dashboard and analytics engine which works on cloud computing
  • IOT practicum and hands on experience on industry standard product development
  • Successfully completing a IOT Edge Computing course at Penn

What we learned

  1. Building an IOT device from the ground up.
  2. The building blocks and technical requirements for developing a complete and generic IOT product
  3. Circuit Design, PCB design and Firmware development using industry standard software and tools.
  4. Sensor Integration, Cloud connections, Wireless Communication and Power Management techniques
  5. Processor, component and material selection and development timeline
  6. IOT design thinking, different phases and challenges in developing a product

What's next for Radiance

We are envisioning of building a minimal viable product and testing it on sight with more powerful sensors and analytics engine. We are planning to create a network of Radiance devices and automate the processes for smart factory. While creating Radiance's MVP, we are expanding the application of device in consumer and retail supply chain sector. Data measurement and predictability will increase the operational reliability, uniformity, cost-effectiveness and safety all while making it easier to control remote locations.

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