The main challenges of sensing in harsh industrial and biological environments are the limited energy of sensor nodes and the difficulty of charging sensor nodes. Simultaneous wireless information and power transfer (SWIPT) is a non-invasive option to replenish energy. SWIPT harvests energy and decodes information from the same RF signal, which is influencing the design of a wireless sensor network. In multi-hop multi-flow wireless sensor networks, interference generally exists, and the interference has a different influence on SWIPT. Route, interference and SWIPT are dependent. However, existing works consider SWIPT link resource allocation with a given route or only select path for one flow without interference. Therefore, this paper firstly analyzes the influence of interference on SWIPT, and select the SWIPT routing with interference. We design an interference-based information and energy allocation model to maximize the link capacity with SWIPT. Then, we design an interference-aware route metric, formulate SWIPT routing problem, and design an interference-aware SWIPT routing algorithm. The simulation results show that as the number of flows increases, there is more likely to obtain performance gains from interference and SWIPT.

Along with the rapid development of smart campus, the deployment of novel learning applications for smart campus requires full consideration of information security issues. Location privacy protection is one of the most important issues, which considers the privacy protection and guarantees the quality of service. The existing schemes did not consider the area of the querying regions for location-based service provider (LSP) during the construction of the anonymous regions, which led to the low quality of service. To deal with this problem, the user’s query range was introduced to present a novel anonymous region construction scheme. In the proposal, the anonymous server first generated the original anonymous subregions according to the user’s privacy requirements, and then merged these subregions to construct the anonymity regions submitted to LSP based on the size of corresponding querying regions. The security and experiment analysis show that the proposed scheme not only protects the user’s privacy effectively but also decreases the area of LSP querying regions and the region-constructing time, improving the quality of service for smart campus.