This platform presents a hardware-neutral way of developing sensing and ubiquitous computing applications. It is focused on making sensing application available to a larger community of users and developers. It is centered around 2 core concepts: a layered approach to system design, and a set of simple network APIs and data abstractions. The design and simple programming model make it possible for novice developers to rapidly design and develop new and creative applications. The project focuses on lowering the knowledge and skill required of application developers that wish to integrate sensor information. It does this through a combination of simple data structures and information models, and a layered network-based API that hides unnecessary details from developers, freeing them to focus on specific tasks.
While commodity sensors and software are becoming more readily available every day, the programming interfaces exported by those systems are tightly bound to the sensors the system supports. Researchers believe that this platform presents a positive first step toward sensing systems that are flexible and general-purpose enough to support a wider array of sensors than is possible in competing systems.
The goal of this project was to investigate the feasibility of using the Owl Platform technology as part of a sustainable business. The Owl Platform, which grew from previous funded NSF research on location-based sensor systems, is a general purpose software stack for building applications using sensed data. Such data often begins with physical observations on quantities such as temperature, humidity, light levels, door/window switches, hydration, and weight. Sensed data can come from many sources, such as small wireless sensors, smart-phones, or cloud applications. The Owl Platform was specifically designed to enable higher-semantic inference from these observations, such as how many people are in a room or when someone is sleeping. Further, Owl eases development of a wide range of applications using sensed data and inferred world-state in diverse areas including elder care, information technology, logistics, laboratory animal care, and emergency medicine. We interviewed many potential customers, suppliers and other stakeholders of sensing applications and technologies in the home sensing, laboratory animal care, datacenter, eldercare, and jewelry markets. We also ran surveys for some of these markets, with the goal of developing a scalable business model for the Owl Platform technologies. For the home sensing and laboratory animal care markets, we also deployed minimum viable systems to get feedback from stakeholders in these verticals. Although we got positive feedback from many potential customers, we found that demand in the home sensing market is too weak to support sensing at the cost points possible with the Owl technology. We also found the value proposition too low in the datacenter and jewelry markets. We found the barriers to entry substantial in the elder-care market. We found that the laboratory animal care market, while small, had the best combination of added value, capital requirements, and low barriers to entry for our team. We thus decided to pursue this market over the others we investigated.
