An integrated smart suit sensor and positioning system electronic Internet of Things (IoT) prototype has been developed to address the growing need for personal welfare monitoring of first-line responders, defenders, and workers exposed to industrial or other hazards, as well as other commercial and defense, and new applications in cloud-based IoT. The system provides a global positioning system (GPS) position map with coordinate data, current Greenwich mean time (GMT) readout, subject's heart rate, body temperature, and a long-wave thermal video camera that provides a forward-looking thermal image. Physiologic data and thermal imaging of the subject may be viewed by monitoring personnel using Internet browser connected to the system's static Internet protocol (IP) address. The system is Wi-Fi connected to a local network, which can be extended to enable secure connection to the Internet with incorporation of additional firmware. Details regarding hardware and software configuration are presented along with an appendix containing additional data. Source code for the software modules currently running on the prototype system is also available for interested parties or potential users and customers.

This chapter is an overview of clustered regularly interspace palindromic repeat (CRISPR) technology and the application of CRISPR sensors with Internet of Things (IoT) in healthcare system. It explains the molecular mechanism of CRISPR technology which is a natural adaptive immune system used by bacteria and archaea against viruses. In genetic engineering, scientist imitates this natural approach to design a novel system which utilizes a single guide RNA (SgRNA) that hybridizes (i.e., bind) with a specific target for cleavage. The binding approach of this system serves as the main mechanism for various CRISPR sensors. Further emphasis is made on the application of IoT in healthcare system using CRISPR sensors. In the future, IoT will change healthcare system using all the data collected from different CRISPR sensors to increase efficiency, lower cost, and provide better life outcomes to patients.

A fast-growing technology with application in science and engineering is Internet of Things (IoT) with digital image processing. Digital image processing is a procedure in which image is taken as an input and provides an output which is also an image but enhanced by applying some technology as per requirement. The main focus of image processing is to take out meaningful information from an input. The use of image processing with IoT is not only in a single field but it spreads all over the area like remote sensing, medical, agriculture, defense, color processing, and industry also. In this chapter, we explain how IoT and image processing can help to find out the disease. In the medical field, it is a very important task to find out disease before diagnosing it. Various types of diseases are found in humans, plants, and animals, so it is important to find out these diseases and provide the best treatment for the disease. In medical, disease diagnosis is a difficult, costly, and time-consuming task, so the use of image processing is used in this field to make it simple and less time-consuming. Disease diagnosis procedure based on image processing with IoT involves some simple steps like image acquition, preprocessing, segmentation, and classification.

WBAN is one the fastest emerging technologies which when applied in healthcare service improves healthcare delivery thereby increasing the lifespan of patients. As an emerging technology, IEEE 802.15.6 provides the guidelines for the WBAN standards: some of which are low power consumption, non-interference, data rate, security, wireless communication, and quality of service. In this research, a review of WBAN with respect to medical applications, architectures, WBAN nodes, WBAN standards, WBAN layers, and acceptable wireless communication technologies are investigated. Some drawbacks of WBAN are power consumption, security, sensor deployment period, expandability, and sensor density. Improving the above WBAN limitations will drastically revolutionize healthcare experiences.

The healthcare data are of utmost importance which need to be maintained safely. The health records of the patients are very confidential and need periodical updates. The data are to be stored in an efficient and secure manner such that it ensures the privacy of the data. Thus the WSNs play a vital role in the medical field in increasing the services for maintaining healthcare. The application of the emerging technology such as blockchain enables drastic improvement in security services thereby enabling efficient healthcare services for effective treatment.

Humans interact and respond to conditions and circumstances around them based on what they see, hear, or smell from their environment. This is why it is important to maintain our senses and protect them from any harm or damage. Any damage we take will either eliminate our sensory organs or cause them to malfunction. Visually impaired people form a large portion of our society. Science and engineering branches are concerned for helping and improving their lives by designing many techniques that can provide them with their daily needs with minimal/no help from other people, which increases their independence and freedom. This design is not a fix but would help to take a step forward in making their life easier and can be a platform for a major breakthrough. The prototype differs from earlier prototypes that use infrared sensors alone, ultrasonic sensors alone, and infrared or ultrasonic sensors with GPS implemented with them. Each prototype has its advantages, disadvantages, materials, and working principle, as it is explained earlier in detail. But the combination of them would improve on the device. The battery in this prototype can be considered as the main disadvantage because it can die unexpectedly anywhere and anytime if it wasn't checked periodically by the user, his family, or caretaker. One of the ways this can be solved with is replacing the battery with solar cells, in any type, normal or bendable, but this will affect the complexity of the device, the whole cost of the device will also increase and this is the main reason they weren't used in the prototype. Voice navigation system can be used in the future to help the visually impaired in a better way and to give them more choices.

Breast cancer is the main cause of increase in the cancer death rate among women globally. Early diagnosis of the breast tumors at premature stages prevents the increase in the mortality rate all around the world. Mammography is currently the most efficient and effective way of diagnosing breast cancers to prevent the patients from unwanted therapies and biopsies. The main objective of the proposed work is to help the radiologist to identify the severity level by appropriate grading of the breast cancers using computer-aided mammography (CAM) techniques. The accurate detection of the breast tumors in the proposed work is done using a modified region growing (MRG) followed by a semantic segmentation algorithm. The proposed system uses two-stage classification systems in which the first stage uses an optimized genetic fuzzy classifier (OGFC) to classify the mammograms as normal and abnormal taking statistical features and the wavelet features as input. Further, the abnormal images are classified to identify the stages of the breast cancer as stage I, stage II, stage III, and stage IV using the second stage classification system which consists of a hybrid neural network optimized using genetic algorithms and trained using the grading dataset taking the shape and size features of the malignant tissue as input. The performance of the proposed system will be analyzed using the true-positive (TP), true-negative (TN), false-positive (FP), and false-negative (FN) values, and accuracy. The proposed system is evaluated using various digital mammograms.

The automatic disease diagnosis system plays a vital role in the detection of diseases in early stages. Computer-aided systems constructed using swarm intelligence metaheuristic approaches have proved their efficiency in diagnosing the diseases due to their strong exploration and exploitation capabilities which help them to find out the optimal solutions. These medical systems that are based on swarm intelligence techniques eliminate the demerits of manual diagnosis systems such as human errors, huge labor and high computational time. These systems have proven to decrease the death rate all over the world by helping the doctors as a second opinion process in complex decision-making situations.

The basic idea of this project is to support blind people in general and to support young people with blindness in particular, where the person will be able to walk comfortably with the use of this smart system. The smart system consists of gloves and shoes, which contain a set of sensors that will alert the user about the existence of any obstacle and also contains a GPS system, which will facilitate access to the person at time and in any emergency. This system will also help the person move and walk easily without using a walking stick.