LAUSR

In the Internet of Things (IoT), connected devices generate a massive amount of data that need to be processed and transmitted to the data aggregator or edge device. The connected devices are resource-constrained in terms of memory, computation power, and energy. In this article, we propose a novel transform using difference sequences. The proposed transform is multiplierless, which makes it very promising for resource-constrained IoT devices. Various properties of the difference sequences, such as orthogonality, linear independence, and circular shift, are studied in detail. These sequences are sparse and take values from the set {0, 1, −1}, which makes these sequences very efficient in computation. Applications of the proposed transform are shown for lossless compression, period extraction, and multiresolution using electrocardiogram, accelerometer, images, and photoplethysmography data sets. Furthermore, the proposed transform is compared with the state-of-the-art data compression transforms.