The sensing layer of the Internet of things based on wireless sensor network requires intensive maintenance over the involved nodes and beyond by the conventional whole-network and periodic model of cluster maintenance. It therefore results in some shortcomings such as high cost of maintenance, heavy waste of energy, full service interruption, and delayed response to incident. This paper proposes a new method, namely, local and on-demand maintenance of clusters (LDMC), to carry out the operations of maintenance only in a restricted range of time and space which is decided by the damaged clusters. LDMC resolves issues such as when to start, which type or who to be maintained by the triggers, pre-processing or different operations of maintenance. The presented scheme is helpful not only to make critical decision on the timing of cluster update, but also to provide in-time response to the change of topology or route of network with the disabled or new nodes. As a result, it allows to reduce the impact of incidents on the function of network, to improve the stability of network, and to cut down the cost of maintenance. Comparison tests are performed on consumption of energy, transmission of data, balance of load and response to incident based on NS2 simulation platform, and the results suggest that the proposed method is able to significantly reduce energy consumption in maintenance of clusters, to prolong the lifetime of network, and to increase the total amount of the transferred data packets.