STEAMSHOP: Advancing Robotics, Embedded Systems, and Digital Electronics

Indiana University of Pennsylvania’s STEAMSHOP makerspace plays a vital role in supporting workforce development initiatives across campus. The space fosters work across a range of projects involving robotics, embedded systems, and digital electronics. STEAMSHOP also collaborates across campus with programs using drone technologies and other computing and data-intensive projects. Through hands-on work with motion, load, and ergonomic sensors, as well as cloud-based processing of drone imagery and orthophotography, students and faculty engage in real-world data collection and analysis. Challenges such as sharing large remote sensing datasets and integrating sensor systems are being investigated. IUP also supports the expansion of workforce training in areas like safety science, robotics, and unmanned aerial systems. By connecting with small manufacturing enterprises, the initiative aims to advance the use of robotics and sensor technologies in regional industries. 

PA Science DMZ potential Use Cases 

Additional network path and path redundancy: 

The PA Science DMZ can act as a secondary path when a primary path exists between customer sites and peers. The PA Science DMZ can provide campuses alternatives to increase resiliency in their wide area networks. 

LAN extensions across different physical facilities: The ability to extend a LAN across physical sites transparently introduces a number of new opportunities that can reduce network infrastructure costs or enable emerging technology. 

Layer 3 network peering between members: Campuses can use the PA Science DMZ to off-load traffic between researchers on KeystoneREN or other Research and Education networks that may otherwise transit the public Internet by establishing BGP peering. Off-loading traffic from an existing commodity service provider can reduce operational costs and enhance network security.

The Pennsylvania Science DMZ (Pa-SDMZ) project will further augment Lafayette College's HPC strategy by facilitating the research data needs of its researchers. Examples of these needs are centered on the ability of researchers to efficiently transfer voluminous amounts of data between institutions and other online entities, segregating these research network flows from campus enterprise network traffic. Such examples include the transfer of hundreds of gigabytes (GB) and the potential for terabytes (TB) of data needed in areas of study ranging from molecular dynamics, to microscopy, and other STEM-related research projects. This work has previously been inhibited by the network limitations available to the College's HPC resources.

Swarthmore College stands to benefit from participating in the project in several ways. First, the dedicated circuit provides a demarcated path for research traffic, enabling faculty, staff, and students to connect with scientific instruments, collaborate within and between institutions, and improve workflows, decreasing time-to-science. 

Science Drivers 

Swarthmore researchers are engaged in several projects that form the basis of relevant science drivers. Some relevant early drivers include:

• Automatically managing workflows related to confocal microscope images, including capture, transfer, analysis, and archiving 

• Improving collection of CryoEM data from multiple sources · Facilitating automated and reliable transfer of biological research data from remote fieldsites back to campus 

• Improving access to, and dissemination of, liguistic datasets of endangered languages

• Automating data transfer and backup among multiple sources for a variety of scientific projects

In the pursuit of Industry 4.0 advancements, DFNK and the Penn State network staff identified a critical need for reliable network performance and robust cybersecurity to safeguard access to manufacturing IoT equipment while maintaining the integrity of PSU’s network. Smart Manufacturing depends on seamless digital integration across resources and processes, leveraging real-time monitoring, control, and predictive analytics to optimize operations. 

DFNK’s Science Drivers focus on secure remote access to manufacturing hardware—both within DFNK labs and at external manufacturing sites. This capability fosters research and education initiatives, accelerating innovation and enabling students and researchers to develop next-generation smart manufacturing solutions.