In recent times we have seen an advent in the number of cases of incidence of diseases such as cancer, diabetes, and genetic diseases. A major cause for the onset of these diseases and their manifestation into life-threatening or disturbing factors is the late diagnosis. We aim to counteract this problem by the following solutions whilst also providing a more healthy environment to live in on a daily basis. Our major consideration is to achieve these solutions in a manner such that they can be integrated into our current way of living and do not provide an impediment or discomfort. Our solution comprises three main points. Firstly, we will use protein markers and gene identification to diagnose cancer and other genetic diseases. A chemical approach to this involves a pill or drug which on detecting the presence of these markers either changes the colour of your urine or stool or produces temporary unharmful machine detectable bioluminescence in the area which is affected by the disease, thus indicating the presence of the disease. Detection can be done by biochemical means. CRISPR is a widely used gene-editing method that can accurately identify the gene that has to be edited We can use this technique for faulty gene detection. A machine learning approach would involve algorithms that have been written to train a Machine Learning model to find data points that will help it predict the presence of the disease. We are also exploring avenues to implement smartphone applications such as RetinaScope and EyeArt to track signs of diabetes by analyzing pupil dilation patterns through smartphone cameras.
Our second solution will diagnose urine related diseases and analyze other data points. The given solution would involve a module attached to the urinal in the washroom. The module will collect a certain quantity of water post-urination. This collected water will be used to wet a dipstick. A photo of this dipstick will be captured by a camera module installation, which will send it to a controller for analyzing the dipstick colour pattern using machine learning and colour quantification technology. After due analysis of the dipstick, the results will be uploaded to the user’s mobile application. In case of any indication of possible diseases is found out, it can be linked to the user’s doctor's application. This method can help in recognizing the onset of diabetes mellitus and kidney-related problems in their very early stages. Moreover, this method will also serve the day to day purpose of analyzing and recommending hydration feedback.
Our third solution presents a method for neutralizing toxins on walls and the general environment of a home by forming a coating on a substrate for deactivation of toxins, the procedure comprising: providing a compound containing a glycoluril functional group and a siloxane monolayer precursor group, applying the compound to the surface, and exposing the surface to microwave electromagnetic radiation.
Our fourth solution is to maintain emotional stability for the people in our intelligent home which involves the use of body heat sensors along with facial recognition sensors with micro-expression detection (like EMOVu ) to sense the energy levels that in turn helps in processing the emotional well being of the people in a room. The collective data will be sent to our app that will compare this data to the preset ideal energy level for a particular room and will inform the user about mood fluctuations and steps to elevate the mood of the room. After getting consent from the user, dispensers fit in every room that are connected to the light panels will use methods of aromatherapy and chromotherapy to maintain a stable and calm atmosphere.
Our final solution is to integrate 3D Printing with Healthcare in Smart Homes. The use of a substance called a ‘Polypill’. A 3D-printed pill, unlike a traditionally manufactured capsule, can house multiple drugs at once, each with different release times. This so-called “polypill” concept has already been tested for patients with diabetes and is showing great promise.
It has been tested for diabetic patients. This application deals with the medication dosage and also solves issues of a diverse drug interaction. For the patient, it eliminates exhaustive monitoring of drug intake when their medications have different schedules. 3D printed pills in the Polypill concept can be very cost-effective.
Utilizing Green Energy, most preferably solar energy, to power the home. Look more into recent advances in solar energy technology like transparent solar panels/coatings of HelioVolt. For our brainstorming and research method, we aimed to answer six essential questions pertaining to our Intelligent Home. Our six questions aimed to provide clarity and deeper insight to the following factors- Target Audience, Versatility, Geographic Location, Customizability, Health Monitoring, and Sustainability.
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