In oceans, fish usually live in an environment that is best suited for their growth. When these fish are introduced into man-made environment, e.g. in mariculture and aquaculture set-ups, the physical parameters might stray from their ideal values, resulting in improper growth and undesired outcomes. Hence, to prevent these undesirable outcomes, continuous monitoring of the physical parameters of the water such as pH, temperature and dissolved oxygen is required. In this work, we present a system called H2O sense, which continuously monitors the physical parameters of the water in tanks and alerts the user in case the values deviate from ideal. We use only low-power, low-cost hardware and open-source development tools, which makes the system easily applicable to various settings. The deployment of our system in the Maritime Laboratory of the University of Namibia shows its efficacy. Furthermore, we evaluate in detail the performance of our system and discuss its applicability in similar challenged environments.
We propose to demonstrate a smart-home solution coupled with a smart-grid that can eliminate the cost of battery backups used in the developing world. We are developing a smart-home application, SoftUPS, that instruments a home and enforces lower levels of power consumption, providing a way for a grid to reduce demand and prevent whole-scale blackouts. We have built hardware to enable such control and will demonstrate this control using a Lab-of-Things application.
This paper targets the unexplored problem of demand response in highly-stressed grids. We present here a novel building DLC system, Aashiyana, that can enforce several user-defined low-power states. We evaluate distributed and centralized load-shedding schemes using Aashiyana that can, compared to current load-shedding strategy, reduce the number of homes with no power by > 80% for minor change in the fraction of homes with full-power.
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