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Biomimicr y is a i eld of study that involves imitating the designs and processes of nature to solve problems using man- made systems. Biomimicr y offer s an empathetic, interconnected under standing of how life wor ks and where we i t in. In bio- inspired designs, the main challenge is to develop a sustainable and effective fr amewor k that can be used in the real wor ld. M ost of the soft robotic designs are state-of-the-ar t models that cannot be used in real sensing applications. In this research, we propose a sustainable sensor-integr ated modular soft robot model that can be used for locomotion and gr ipping applications. This wor k presents the steps involved in modeling, designing, and fabr icating soft and l exible end effector s that can be used for soft robots with integr ated soft stretchable sensor s. We demonstr ate the design methodology involved in modeling and simulating the proposed model for robots that would require effector s with increased functionalities. 

Sitting is the most common status of modern human beings. Many people are sitting with bad posture which may lead to postural pain. Especially for people with short term-disabilities, sitting in the right posture is very important. In this research, we propose a posture recognition system on an office chair that can categorize different health-related sitting postures to prevent harm from bad sitting postures. The smart chair system consists of an array of five flex sensors integrated into an FPGA board. The output of the system is the classification result of the sitting posture. In this paper, several health-related sitting postures are selected. The sitting postures are: 1-sit straight; 2-left recline; 3-right recline; 4-lounge;5-lean backward; 6-cross left leg; 7-cross right leg. The proposed reconfigurable framework will be integrated as part of smart ambient assisted living with user-centered health monitoring system. 

This paper proposes a reconfigurable framework to automated reconfigurable secure home system. The proposed system has 3 main features: monitoring controlling of smart home automation through password-protected door lock system, the monitoring controlling of day-to-day electronic devices, fire safety with room temperature monitoring and antitheft system. In this paper, different sensor combinations are to be integrated with the FPGA board. For the Fire safety module, a temperature monitoring sensor has been used that will display the temperature continuously. If the temperature in the room exceeds 60 degree Celsius, then it will turn on the buzzer or alarm for fire safety. For the Anti-theft system, infrared (IR) sensors are fitted in each window. If any unauthorized person tries to breach through the window, both IR sensor signals will be turned ON and the output of the buzzer goes to high. For the door lock system, a finite state machine (FSM) has been implemented. This work focuses on a scalable smart home automation framework using the FPGA board that can be used for integration of multiple sensors in a cost-effective way. The research in this project is focused on processing multiple analog sensor inputs through the FPGA board.