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The Indian population is rapidly growing especially in the urban area. The most of the rural population is shifting to the urban area leads to the construction of new municipalities and rehabilitation of existing cities. The Indian Government as a result of this committed to the development of “Smart cities mission”. The increase in population leads to an increase in generation of waste and this may impact on public and environment health. The key factors responsible for the generation of this waste are industrialization, urbanization, and growth in an economic way. The current systems of waste management in India are not that much efficient which may lead to an overflow of waste in most of the places. A clean and hygienic environment is essential for health and provides clean living space. The remedy for this problem is a “Smart bin”. Hence, an IoT enabled Smart waste management system is proposed and its performance is analyzed.

The Internet of Things is a networking framework which allows the physical objects to connect with existing networking infrastructure. Due to high heterogeneity of hardware and communication protocols present among the things, poses many areas of the layered architecture to be re-engineered. Existing cross layered architectures for Sensor/Ad hoc networks cannot be applied directly, as the network characteristics are different. Internet uses hierarchical architectures whereas the Sensor/Ad hoc networks use flat architectures. In our work, we propose a cross-layer architecture of data-link and network layers for delay sensitive applications, such that response time should be less. An agent-based architecture was looked in, to optimize the inter-relation among the things, to find an optimal path i.e., optimize the end-to-end delay. IoT network mainly follows star type of topology but sensor network is multihop. The results show that the methodology we started with will yield good results for delay sensitive applications.

With a rapid increase in IoT devices and smartphone technologies, the IoT connectivity is redefined. The connectivity is no more simple establish and terminate a call on a telephone/mobile network. IoT connectivity has opened a new dimension on telecom network referred to as an interactive connectivity where i) the user interacts with smart devices/phones to accomplish a task. ii) the smart devices/phones interact with IoT edge devices for information/functionality. iii) smart devices interpret the data with real-world data to complete the task. In the project, offloading the data between IoT edge devices and smart devices/phones/gateways for completing a task is proposed in an energy and communication efficient way. The energy consumption in these edge devices can be reduced by the proposed model and the results are encouraging.

Arsenic (As), is a worldwide societal & environmental threat and therefore requires continuous monitoring in the natural water resources. Although, many opto/electrochemical techniques based on, macro, micro and nanostructures have been developed for the detection of As3+ ions, with advantages of high selectivity, sensitivity, and fast response. Yet, most of them are commercially unavailable, expensive and requires harsh operational conditions. Herein, we report ours first results on novel nanocomposite (NC) material, reduced graphene oxide (rGO)/manganese oxide (MNO2), for sensitive and selective detection of As (III) in water. The novel MnOx/rGO nanocomposite based working electrode is fabricated by one step electrochemical reduction method and characterized for its optical, structural and electrical properties. Results demonstrated a reduction peak at −1.4 V in sodium sulfate electrolyte, confirming simultaneous reduction of manganese and grapheme oxide (GO) on GO modified glassy carbon electrode. Preliminary sensing results revealed, sensitivity of fabricated electrode towards As (III) by appearance of stripping peak at ∼ 0.26 V in square wave anodic stripping voltammetry (SWASV). Furthermore, sensing parameters such as time, pH, and deposition potential are optimized, which are recorded to design a portable embedded system for As (III) sensing.

This paper is aimed at presenting the car-integrated framework in which the validation of automobile applications as well as driver's health condition is measured using different stimuli. And additionally, the mechanical parameters are detected as engine failure, brake failure etc. It is also an essential one for both vehicle and the driver's safety measure like accident avoidance in the realistic driving conditions. Context information is important for two reasons: first, it helps to interpret driving situations during data processing. Second, we expected this information to be useful to assess the signal quality of the physiological data.

In the present work, the effect of the surfactant concentration and particle size on the 2D assembly and corresponding isotherms of the silica nanoparticles at the air/water interface is studied and reported using Langmuir-Blodgett (LB) technique. Silica nanoparticles (NPs) of different sizes (30 nm & 150 nm) were synthesized by Stober's method and were characterized to determine their sizes and dispersity using scanning electron microscopy. As-synthesized NPs were hydrophobized to varying extents through addition of varying amounts (0.5 mg to 1.5 mg) of cationic surfactant, cetyltrimethylammoniumbromide (CTAB). The lift off area (area/particle) and corresponding yield was found to be very low for 30 nm sized particles. The yield in case of 150 nm sized particles participating in monolayer formation is found to be much higher implying a more optimal interaction with surfactant in the studied concentration range. The low yield at small particle size can be attributed to the partial surface modification of particles.

Gold – poly(dimethylsiloxane) (Au – PDMS) nanocomposite freestanding films were prepared and used to study the binding of Human Serum Albumin (HSA) to polyclonal anti-HSA. A new method of synthesis was developed for sensing application when most of the gold nanoparticles have to be localized in the surface layer. The localized surface plasmon resonance band in gold nanoparticles is used to monitor the binding reaction. SEM and AFM images as well as the UV- Visible spectrum have shown that incubating the PDMS film in a diluted solution of chloroauric acid for 18 hours results in a good dispersion of gold nanoparticles on the polymer surface, without aggregation. The kinetics of the formation of Au-PDMS is studied by UV-Visible spectroscopy. Biosensing experiments carried out with the Au-PDMS composite showed a good sensitivity allowing the detection of 2.5 mg of antigen. Compared to the previous methods of fabrication, the present technique has the advantage of simplicity; the structures can be prepared under mild conditions and without using an external capping agent. The method is suitable for microfluidic sensing applications for a variety of biomolecules.