Complexity of embedded systems is growing with increasing demands on computation at lower cost, lower power and longer battery life. Today’s systems do not normally run just a single task at a time but multiple tasks together by sharing the limited resources (CPU, memory, hardware modules, battery life) available on an embedded platform. Most of the published works explore various architectural optimizations to pack more tasks together and meet the given specifications. However relaxing application specifications can open up a completely new and vast design space wherein application specifications do not just remain just as constraints but becomes objective parameters to optimize for. Here, we introduce a complex device named MAVI being designed to assist visually impaired pedestrians in their outdoor mobility. We explain the complex design space of this device to establish a case for exploring the tradeoffs between application behavior and associated QoS across tasks. An efficient system level design space exploration framework is needed to exploit interaction between these tasks which can possibly lead to efficient use of limited resources.