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This paper presents the development of a cost-effective automatic system for greenhouse environment control. The architectural and functional features were analyzed in the context of the realization of a controlled-environment agricultural system through all its stages: installation, deployment of the software, integration, maintenance, crop control strategy setup and daily operation of the grower. The proposed embedded platform provides remote monitoring and control of the greenhouse environment and is implemented as a distributed sensing and control network integrating wired and wireless nodes. All nodes were built with low-cost, low-power microcontrollers. The key issues that were addressed include the energy-efficient control, the robustness of the distributed control network to faults and a low-cost hardware implementation. The translation of the supervisory growth-planning information to the operational (control network) level is achieved through a specific architecture residing on a crop planning module (CPM) and an interfacing block (IB). A suite of software applications with flows and interfaces developed from a grower-centric perspective was designed and implemented on a multi-tier architecture. The operation of the platform was validated through implementation of sensing and control nodes, application of software for configuration and visualization, and deployment in typical greenhouses.

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Peritoneal Carcinomatosis (PC) is an abdominal cancer for which cytoreductive surgery followed by hyperthermic intraperitoneal chemotherapy (HIPEC) proved to be a promising treatment. HIPEC requires the intraperitoneal spread of cytostatic solution at high temperatures (41-43˚C) accomplished within 60-120 minutes, during surgical interventions. This paper presents the heating system's identification, by using a graphical fitting method on a temperature measured signal, for a HIPEC device intended to be developed. Also the design of two PID temperature controllers is presented, using the Strejc design method and the Ziegler-Nichols method. The two feedback control structures are compared via simulation, based on their step response signals and their overall performances.