In this paper, SmartHealth and Safety Monitoring System is presented, which is a novel maintenance system for the early detection of H&S devices that are in critical state. The proposed system uses smart sensors for data collection and status monitoring. The goal is to monitor the status of consumable items, such as plasters and sterile wipes, in first aid boxes by monitoring the total change in box weight, level of earplug dispenser or weight change of a fire extinguisher. The battery state (i.e., remaining charge) is also monitored because H&S monitoring systems are equipped with smart sensors which run on batteries. The proposed prototype achieves high efficiency by using a genetic algorithm (GA), ant colony optimisation (ACO) algorithm and travelling salesman problem (TSP). With these algorithms, the system can find the shortest path within a short time and then access the facilities whose devices are critically low and thus require maintenance or replenishment. Furthermore, artificial neural networks to predict the optimal performance of the system and the correlation between effective input factors and performance output.
Abstract— Health is the most important factor in every living life. This paper proposes smarthealth monitoring based on GSM which uses ARM7LPC2148 controller. There are many parameters that are to be monitored. Here three parameters are taken for consideration, namely Heart rate, BP and Body temperature. The sensed data will be notified through SMS using GSM and displayed through LCD and also by Buzzer.
We have developed an expert system called SmartHealth Prediction system, which is used for simplifying the task of doctors. A system checks a patient at initial level and suggests the possible diseases. It starts with asking about symptoms to the patient, if the system is able to identify the appropriate disease then it suggests a doctor available to the patient in the nearest possible area. If the system is not sure enough, it asks some queries to the patients, still if the system is not sure then it will display some tests to the patient. Based on available cumulative information, the system will display the result. Here we use some intelligent data mining techniques to guess the most accurate illness that could be associated with patient’s symptoms and based on the database of several patients medical record, algorithm (Naïve Bayes) is applied for mapping the symptoms with possible diseases.
With this system, patient can be independent as their family members, friends and health consultants do not have to worry for not being by patient’s side all the time to make sure that patient is fine. This SmartHealth Alert System (SHAS) is beneficial as it decreases the risk of death in people’s life.
This paper proposes a low cost, wearable and portable smarthealth monitoring system in real time. SmartHealth Monitoring System is IoT based system which makes use of sensors and cloud storage. Data obtained from sensors is stored on cloud, where individual records are separated and Naïve Bayes Algorithm is applied to detect the disease. This system monitors health of normal people rather than only focusing on the patients and allows people to be mobile in their working environment. Person’s health is continuously monitored using wireless sensor networks and the obtained data is transmitted to microcontroller unit which is then sent to cloud storage. Proposed system consists of pulse rate sensor, body temperature sensor and blood pressure sensor. Using these parameters and by applying Naïve Bayes algorithm any sudden change in person’s health will be notified to doctor through SMS using GSM connection.
This application allows user to get instant supervision on their health issues through an smarthealth care application online. The application is feed with various symptoms and the diseases associated with those systems . Patient can check their medical record Hence, this system provides Quality Health Care to everyone and error free and smooth communication to patients[3,4]. Mobile technology is also use in hospital management by serving with search hospitals; improve health outcomes and medical scheme efficiency measures.
http://www.ijmr.net.in email id- firstname.lastname@example.org Page 374 to care, increase quality of care and most importantly reduce the cost of care. The Internet of Things (IoT) is the systems that connect with internet in an exchange of information, tracking, monitoring realizing localization in the health care management. The strong factor of SmartHealth Care is the extent of coverage it can provide anywhere in the world. It is a concept of connecting anyone, anything, anytime, anyplace, any services and any network. It is the concept of next-generation that can have great impact on the lifestyle of human being through interconnection. The connectivity of Smart phones, tablets and laptops via 3G/4G connected to a network will play a large role to improve access to health care and involving patients in their own treatment. A good example of SMARThealth program of George Institute for Global Health India in collaboration with Institute of Biomedical Engineering of the University of Oxford was implemented in Andhra Pradesh. The Village health workers went a short training based on that program and they have shown much better results in accurate identifications and selection of treatment. The Internet of Things (IoT) is set to revolutionize the health-care industry all over the world. Thereby, the SmartHealth Care can transform the health care of villages in the following ways:
The implemented device is relevant in the field of smarthealth since it addresses the issue of non- adherence with medication regimens. As mentioned in Section 2.2, medication adherence is key in achieving optimal treatment results. However, around 20% to 50% of patients do not take their medication as indicated by trained professionals. In the long term, this can lead to higher hospitalization rates and treatment costs, especially for patients with chronic illness. The touch sensor integrated into the smart medication cap prototype registers input when a user opens the medicine bottle to take their medication. This triggers a notification which is received by the SmartMed android application which will record a detailed timestamp saved into a database. This way, the smartphone application keeps a detailed record of when medication has been taken (i.e. when the touch sensor registers input).
The project entitled “SmartHealth Monitoring And Locating System” is an effective health monitoring and locating system for a soldier which is made by integrating the advancements in wireless and embedded technology. It helps for a successful secret mission as well as on training field. This system can be used in critical conditions. It has real-time capability. The accuracy of system is affected by some factors such as weather, environment around the mobile soldier unit, GPS receiver. The future works include optimizing the hardware system, choosing a suitable GPS receiver and transfer speed for accurate ECG representation.
the data to the power provider for observing and charging. Shrewd meters ordinarily record vitality hourly or all the more as often as possible, and report in any event every day. Savvy meters empower two-path correspondence between the meter and the focal framework. Such a progressed metering foundation (AMI) contrasts from programmed meter perusing (AMR) in that it empowers two-path correspondence between the meter and the provider. Correspondences from the meter to the system might be remote, or by means of settled wired associations, for example, control line bearer (PLC). Remote correspondence alternatives in like manner use incorporate cell interchanges (which can be costly), Wi-Fi (promptly accessible), remote impromptu systems over Wi-Fi, remote work systems, low power long range remote (LORA), ZigBee (low power, low information rate remote), and Wi-SUN (Smart Utility Networks).
Community mental health groups, crisis and home resolution teams, assistive outreach teams and early psychosis teams all play a key role in preventing costly inpatient admissions. If any changes are not dealt with early, the prognosis is often worse and, as a result, costs for treatment will undoubtedly be higher . An early intervention approach has been shown to reduce the severity of symptoms, improve relapse rates and significantly decrease the use of inpatient care. Evidence suggests that a comprehensive implementation of Early Intervention Practice (EIP) in England could save up to £40 million a year in psychosis services alone. Being able to detect deteriorating conditions in dementia patents earlier, enables physicians to better diagnose and identify stage progression for the disease. This enables earlier intervention for the illness before cognitive deficits affect or worsen mental capacity; supporting the individual and their family in adapting to the illness simultaneously.
The end-to-end connectivity using sensors and other devices in healthcare is shown in Fig 2. Most of the users are using smart phones with built-in sensors. The model provides platform for physical sensors, which are connected directly with patient’s smart phone to obtain data at run time. This data is processed and stored in the cloud storage. The stored data can be accessed by practitioners and medical staff later on to observe and monitor patients’ health. There are many cases where a system like this can be used. This is able to use the wearable devices and smart phone sensors to collect the patient data, which is integrated with Internet of Things. In our case, a patient used built-in Heart Rate sensor of his/her smart phone like Samsung Note 4 / S4 to get health related data. The data displayed on the screen of the smart phone, and sent automatically to cloud storage for processing and storing using 3G or Wi-Fi. Machine learning algorithms are applied on data to verify the conditions of the patient. If the value is out of the normal range, then an alert message is sent to a doctor/physician and the doctor will take appropriate action accordingly.
These interconnected IoT gadgets deliver huge sums of data that ought to be managed productively by the suppliers and so could be an enormous challenge. To overcome this challenge of putting away and analyzing expansive information, the procedure of Internet of Things Analytics (Particle) is executed. The crude data is converted into valuable and restoratively important information utilizing the methods like information extraction and information analytics. In truth, it has been anticipated that by 2020, more than 50-55 percent of techniques used to analyze raw data will make better use of this influx of data which is generated from instrumented machines and applications. In order to manage and care for our wellbeing, the IoT movement depends on a few empowering innovations. Collection of real-time information from different sources, in this case, boundless numbers of patients over an expansive period of time, must become exceptionally simple and quick utilizing the potential of IoT. The power of IoT for health and medical services is controlled by Smart sensors that accurately measure, monitor and analyze a range of health standing indicators. These indicators will embrace basic important health signs like pulse rate and blood pressure, oxygen and glucose level in the blood and heart rate. Smart sensors are often incorporated into medicines and pill bottles that are connected to a network and might generate alerts concerning whether or not the patient has taken a scheduled dose of medication.
Acceleration information also varies for similar activities, thus making it extra difficult to finely differentiate certain type’s activity. A major challenge in the design of ubiquitous, context-aware smart phone applications is the growth algorithms that can find the person movement state using noisy and equivocal sensor information. Limits have been found in the range of movement activities recognized by use of single sensor mainly and; due to the difficulty of person movement and noise of sensor signals, movement categorization algorithms tend to be probabilistic.
Since the first definition given by Ashton in 1999 at MIT Auto-ID Center, IoT has evolved significantly and become a reality thanks to its key technologies such as WSN, RFID, and cloud computing which facilitate its integration into existing systems. In this context, IoT applications involve a wide range of areas such as security and surveillance, environmental monitoring, medical and healthcare, SHM, agriculture, logistics and transportation, manufacturing, etc. IoT-based applications rely on the creation of smart environment and things such as smart homes, smart cities, smart infrastructures, smart transport, smarthealth, smart grid, and smart products. One of the well-known applications of IoT is in the healthcare sector, with the development of applications running on electronic devices, which combine sensors and mobile phone as a platform to monitor in real-time personal health status.
To beat the downside of existing framework we have created smarthealth prediction System. We have built up a specialist framework called SmartHealth Prediction framework, which is utilized for improving the task of specialists. A framework checks a patient at initial level and proposes the possible diseases. It begins with getting some information about manifestations to the patient, in the event that the framework can distinguish the fitting sickness, at that point it proposes a specialist accessible to the patient in the closest conceivable territory. On the off chance that the framework isn't sufficiently sure, it asks few questions to the patients, still on the off chance that the framework isn't sure; at that point it will show a few tests to the patient. In light of accessible total data, the framework will demonstrate the result. Here we utilize some intelligent minin methods to figure the most precise disorder that could be associated with patient's appearances and dependent on the database of a couple of patients restorative record, calculation (Naïve Bayes) is connected for mapping the side effects with conceivable diseases.This framework improves undertaking of the specialists as well as helps the patients by giving vital help at a soonest organize conceivable.
In day-to-day life most of the people need to take medicines which was not there in past couple of years and the reason behind this is diseases are increasing in large amount. So sooner or later many people come in contact with these diseases. Some diseases are temporary diseases while many are permanent life threatening diseases. Life threatening diseases gets mixes with the human body in such a way that they can’t leave the body ever and they increases in rapid time. Life span of humans became less because of such diseases and to overcome or to live a better life we need to take medicines regularly and also in large amount. We need to be in advice of Doctor who tells us to take desired pills in desired way so that patients face problems like forgetting pills to take at right time and also when Doctor changes the prescription of medicine patients have to remember the new schedule of medicine . This problem of forgetting to take pills at right time, taking wrong medicines and accidentally taking of expired medicine causes health issues of patient and this leads to suffer from unhealthy life.
Moreover, smart contract allows all users query the information. For consumers, it provides the function to get databases name, dataset size, owners. Which used to help consumers to select the suitable databases and the necessary information to start a trade. Another function used to get their balance, consumer confirm the money transfer process completed or failed, or they need transfer more coins to start the next trade. Like consumer, contract also provides the similar functions to get producer’s profile including balance, dataset size etc. However, the most important are the buyer’s information, based on this, producers can know whether exist any new buyer, how many data and how long should they provide and where to send their data. To help data producer know how and when their data used, a function for consumers to record their research events deployed, which involved producers’ personal data. Consumer can call this function by simply fill their name, the time of the event, databases name, event description. They can use the minimal gas to send this transaction; it can be very helpful for producers to know what happens with their person data. However, it is not a mandatory function. All users can check the specify consumer’s events by call checkEvent() function.