I have worked on a paper which utilizes concepts from signal processing and machine learning, and then implements them in a low-cost embedded system. Since the work was more on the implementation side, it required less mathematics and more engineering. Furthermore, since I was using hardware from a particular company which suited my application the most, among other contenders in peripherals and price, the implementation is really hardware-dependent. Finally, I cannot seem to find similar work. In that way, it is a bit novel. Is this something which will be acceptable for say, IEEE Transactions in Industrial Electronics?
"Stitching together" some existing algorithms is not necessarily bad, if the combination is both valuable and non-trivial. It can be argued that a lot of today's research in computer science is mostly stitching together ideas that have existed for a long time. Further, I am a huge opponent of the notion that it is somehow better / scientifically more valuable to come up with your own (almost always inferior) algorithms for well-known standard problems just so that one can claim to have a higher "novelty".
That being said, it is of course hard to answer your question without knowing the concrete work. As a rule of thumb, read through a number of back issues of your selected journal. If all of them seem to have a much broader contribution than what you have in mind, your idea may be too small (but don't let the impostor effect get you, either).