Internet of Things (IoT) is a phenomenon involving connecting things or objects with sensors. The IoT market is growing rapidly, and there are strong incentives for companies to follow the trend of IoT growth and development. However, the percentage of IoT measures that are considered successful seems low. The complexity of carrying out an IoT project lies in the need to adjust all the pieces of the puzzle: assets, sensors, communications, technology, coverage, and geographical locations with precision of the measures and regulations. All these requirements determine the economic viability of the business and its benefit. This study, therefore, examines how the project methodology can support the development of the concept and ensure the business value of IoT initiatives. The project methodology developed in this study is called PoC Design. A case study was evaluated, in which defects in street lighting were investigated and carried out. The evaluation of the methodology highlighted the importance of defining problems and solutions based on business value, calculating the potential of an IoT initiative, determining the continuation of the project, involving stakeholders at an early stage, and creating a PoC to validate the concept with stakeholders.
With the increasing use of wiretess technologies, image comprission requires higher performance supported with new features to accommodate the bandwidth and low power requirements of personal mobile devices. To address this need in the specific area of still image encoding, this paper introduces a second level compression scheme upon an image, which is already compressed using an existing algorithm. In the proposed technique, error concealment of digital images implemented by adopting the NFD information hiding technique is pedormed in the initial phase, followed by conventional transform based encoding and enuopy encoding to achieve the first stage compression. The main contribution of this paper is the second level compression (named PGR compression by authors) of the entropy encoded image wherein the bit positions of the encoded image are subjected to a mapping procedure with the matched bit positions in a base file (known both the transmitting and receiving mobile devicdstafions) to generate a mathematical function which would tit the mapped data set. The conversion of the original image file in to a mathematical function requiring fewer bits provides very high compression.
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