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In order to design a 3-DOF hybrid bionic manipulator based on joint reintegration and bearing capacity. Firstly, the coordinate system of the 3-DOF hybrid manipulator is described, the vector method is used to solve the kinematic positive solution of the manipulator so as to express the pose of the end-effector based on the base coordinates. Second, the workspace of 3-DOF hybrid bionic manipulator is solve, and the workspace distribution map of 3-DOF hybrid bionic manipulator is obtained. The workspace analysis results shows the workspace of 3-DOF hybird bionic manipulator is fan-shaped and nearly symmetrical, structural parameters with larger workspace are obtained. Finally, a virtual prototype of the bionic manipulator is designed based on the obtained structural parameters. The manipulator has good alignment and stability, and can be used in a variety of scenarios.

One of the most important aspects of Gerontechnology is to support the elder who lives alone at home. According to the elder's relatively obvious and stable routine of daily activities, this paper proposes a statistical approach based on machine vision to build an Elder Indoor and Outdoor Activity Model (EIOAM) through analysis of the elder's daily activity data in the main activity places and the entry/exit places collected by the Omni-directional Vision Sensor (ODVS). Since the elder's daily routine varies with the alternating of seasons and growing of age, the model should learn the routine of activities adaptively. This model is able to detect and predict the abnormal activities of the elder through detecting the significant deviations of the activity data in spatial and temporal aspects. By using this model, one can not only detect the abnormal activities happened in sight of the vision sensor (indoor), but also out of sight (outdoor). Thus provides a new methodology for the remote home care of the elder who lives alone.

Water quality monitoring is of great importance in water safety protection and water emergency supervision. Water quality can be reflected by aquatic creatures' ecological status, especially fish's, directly and synthetically. Therefore, aquatic creatures' ecological status can be used to monitor water quality safety. This paper presents an real-time water quality monitoring technology in which computer image processing technique, network communication technique and observation of aquatic creatures' ecological status, such as small fish's, technique are used. A machine vision based biological water quality monitoring equipment is proposed. It monitors water quality safety by observing fish's biological status. This new water quality monitoring technology overcomes the shortages of existing water quality monitoring technology, which is costly, and inapplicable to large-scale long-term and on-line water quality monitoring. Thus, it provides an economical and effective method for water quality monitoring, water safety protection and water emergency supervision.