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The internet of Bio-Nano things
Abstract and Figures
The Internet of Things (IoT) has become an important research topic in the last decade, where things refer to interconnected machines and objects with embedded computing capabilities employed to extend the Internet to many application domains. While research and development continue for general IoT devices, there are many application domains where very tiny, concealable, and non-intrusive Things are needed. The properties of recently studied nanomaterials, such as graphene, have inspired the concept of Internet of NanoThings (IoNT), based on the interconnection of nanoscale devices. Despite being an enabler for many applications, the artificial nature of IoNT devices can be detrimental where the deployment of NanoThings could result in unwanted effects on health or pollution. The novel paradigm of the Internet of Bio-Nano Things (IoBNT) is introduced in this paper by stemming from synthetic biology and nanotechnology tools that allow the engineering of biological embedded computing devices. Based on biological cells, and their functionalities in the biochemical domain, Bio-NanoThings promise to enable applications such as intra-body sensing and actuation networks, and environmental control of toxic agents and pollution. The IoBNT stands as a paradigm-shifting concept for communication and network engineering, where novel challenges are faced to develop efficient and safe techniques for the exchange of information, interaction, and networking within the biochemical domain, while enabling an interface to the electrical domain of the Internet.
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... The advancement of devices ranging in size from one to several hundred nanometers is made possible by nanotechnology. At this size, a nano-machine is the simplest functional unit made of nano components that can carry out easy operations like sensing or actuation [2]. The development of nanotechnology has led to the creation of nanodevices, which are made of nano components and are capable of sensing or actuation. ...
... IoT is essentially brought down to the nanoscale by combining it with nanotechnology, which is how the idea of IoNT originates. IoNT uses nanosensors, sometimes known as "nano things," that are linked by a nano-scale network and communicate with each other via nano-communication technologies [2]. An IoT system is made up of several networked sensors that collect data on their own and exchange it with other sensors via the cloud. ...
... IoNT consists of nano nodes, nano routers, gateways, and nano-micro interface devices and the communication between the components are presented in figure 2. a) Nano nodes: The most small and most fundamental kind of nanomachine is a nano-node, which can carry out very simple processing, store a tiny quantity of information storage devices, and transfer the information to a very small distances due to its limited bandwidth and power. Biomedical nanosensor nodes found in human bodies and nano machines with communicating capabilities incorporated into a smart home devices are two examples of nano-nodes [2,4] b) Nano routers: Nano-routers possess more omputational capabilities than regular nano-nodes. It acts as information aggregators in an IoNT network. ...
INTRODUCTION: Internet of NanoThings (IoNT) is regarded as the next generation of the Internet of Things due to its bright future and wide range of applications . According to the global "Internet of Nanothings (IoNT) Market" research, there has been good growth in recent years, and this trend is expected to continue until 2030. IoNT is basically the Internet of Things on a nanoscale. IoNT essentially describes how nanoscale devices are connected to one another within current networks. A high-speed network can be used to connect different nanodevices through the IoNT. This study provides a comprehensive overview of the architecture, benefits and applications of IoNT. OBJECTIVES: The objective is to provide insights into IoNT framework and it applications in fields like healthcare, food industry, agriculture , environment monitoring etc, METHODS: This study explored the IoNT architecture and its applications. The exploration involves reviewing the articles, journals and other web resources. RESULTS: Highlights the aspects of IoNT and emphasizing the importance of its applications in various fields. The need to combine this research and emphasize the IoNT related applications stems from the dearth of research in the field. CONCLUSION: The world is becoming increasingly developed as a result of ongoing technological advancements. Future developments, which are expected to peak in the next one to two decades, will be led by IoT and nanotechnology. IoNT offers potential and means to enhance numerous facets of individuals' lives. Its primary characteristics are monitoring and diagnostic services, which support and improve decision-making and outcomes across a range of application domains.
... As a biocompatible, energy-efficient and natively nano-scale solution, DBMC could facilitate information exchange in a future internet of bio-nano-things (IoBNT), where biological environments like the human body are accessible to networking. The realization of the IoBNT could enable revolutionary medical use case such as targeted drug delivery or advanced monitoring and diagnosis [1], [2]. Nodes within these DBMC networks are expected to be natural or synthetic structures on the micro-and nanoscale. ...
... Nodes within these DBMC networks are expected to be natural or synthetic structures on the micro-and nanoscale. The field of bioengineering has seen significant progress in recent years and engineered cells or bacteria can function as devices with specific but limited capabilities [1]. To realize the envisioned complex applications, the establishment of DBMC networks for communication and cooperation is necessary. ...
Proposals for molecular communication networks as part of a future internet of bio-nano-things have become more intricate and the question of practical implementation is gaining more importance. One option is to apply detailed chemical modeling to capture more realistic effects of computing processes in biological systems. In this paper, we present ChemSICal, a detailed model for implementing the successive interference cancellation (SIC) algorithm for molecular multiple access in diffusion-based molecular communication networks as a chemical reaction network (CRN). We describe the structure of the model as a number of smaller reaction blocks, their speed controlled by reaction rate constants (RRCs). Deterministic and stochastic methods are utilized to first iteratively improve the choice of RRCs and subsequently investigate the performance of the model in terms of an error probability. We analyze the model's sensitivity to parameter changes and find that the analytically optimal values for the non-chemical model do not necessarily translate to the chemical domain. This necessitates careful optimization, especially of the RRCs, which are crucial for the successful operation of the ChemSICal system.
... M OLECULAR communication (MC) or particle-based communication, a paradigm inspired by nature, has emerged as a promising solution to communicating with biological organisms where traditional communication methods have been shown to be ineffective [1], [2], [3], [4]. By leveraging biochemical mechanisms for the transmission of information, MC is also believed to play a vital role in the realization of the Internet of Everything (IoE) [5], particularly the Internet of Bio-Nano Things (IoBNT) [6], [7], and the concept of digital twins through the extension of connectivity to nanoscale and biological environments [8]. This unconventional bio-inspired technique encodes information with one or more types of information molecules (IM) at the transmitter end, which are then propagated to a receiver through various mechanisms such as channel diffusion [9], [10], [11], [12], [13], mimicking methods of communication commonly found in the natural world. ...
... • Brain-Machine Interfaces (BMI): High-fidelity signal transmission in neural interfaces for advanced prosthetics and various other cases of medical and non-medical use [3], [14]. • Internet of Bio-Nano Things (IoBNT): Robust communication between nanoscale device networks in complex biological environments [6], [7]. • Environmental Sensing: Deployment in environmental monitoring systems to detect pollutants or biochemical agents with high sensitivity [53], [54]. ...
Molecular communication (MC) in microfluidic channels faces significant challenges in signal detection due to the stochastic nature of molecule propagation and dynamic, noisy environments. Conventional detection methods often struggle under varying channel conditions, leading to high bit error rates (BER) and reduced communication efficiency. This paper introduces ART-Rx, a novel Adaptive Real-Time Threshold Receiver for MC that addresses these challenges. Implemented within a conceptual system-on-chip (SoC), ART-Rx employs a Proportional-Integral-Derivative (PID) controller to dynamically adjust the detection threshold based on observed errors in real time. Comprehensive simulations using MATLAB and Smoldyn compare ART-Rx's performance against a statistically optimal detection threshold across various scenarios, including different levels of interference, concentration shift keying (CSK) levels, flow velocities, transmitter-receiver distances, diffusion coefficients, and binding rates. The results demonstrate that ART-Rx significantly outperforms conventional methods, maintaining consistently low BER and bit error probabilities (BEP) even in high-noise conditions and extreme channel environments. The system exhibits exceptional robustness to interference and shows the potential to enable higher data rates in CSK modulation. Furthermore, because ART-Rx is effectively adaptable to varying environmental conditions in microfluidic channels, it offers a computationally efficient and straightforward approach to enhance signal detection in nanoscale communication systems. This approach presents a promising control theory-based solution to improve the reliability of data transmission in practical MC systems, with potential applications in healthcare, brain-machine interfaces (BMI), and the Internet of Bio-Nano Things (IoBNT).
... This shift is particularly crucial as we encounter an explosion of data from numerous devices and sensors connected through the Internet of Things (IoT). With the introduction of molecular communications (MCs), where information is encoded into molecules rather than electromagnetic (EM) waves, we saw the introduction of the Internet of Bio-Nano Things (IoBNT) [1] that elevates IoT by interconnecting to engineered biological systems, expanding our paradigm of computing devices that are built from natural biological components. ...
As the world searches for groundbreaking, unconventional computing technologies, especially for intelligent edge applications, biological AI is emerging as an energy-efficient, robust, and reliable alternative. Researchers have unveiled the immense computing capacity inherent in biocomputing elements such as bacterial cells. The computing power of bacteria can be harnessed through Gene Regulatory Neural Networks (GRNNs). Biofilms, acting as sophisticated collections of GRNNs, leverage the natural distributed computing architecture with capabilities like parallel processing and analog computing in individual cells while consuming very little energy relative to conventional computing systems. This study introduces the concept of Biofilm Living AI Devices (BLAIDs), which proposes engineering biofilms using optogenetics to function as self-sustaining AI edge devices that interface with modern telecommunications architectures. Our simulation-based analysis demonstrates the computing complexity and reliability of BLAID, establishing it as a compelling candidate for the next generation of low-energy computing and advanced AI technologies.
... M OLECULAR communication is envisioned to play an important role in future communication networks as a biocompatible, energy-efficient way to transmit information in biological, micro-and nanoscale environments. In a future Internet of Bio-Nano Things (IoBNT) so-called Bio-Nano Machines (BNMs), enabled by recent advances in nanotechnology and bioengineering, could cooperate and communicate to achieve complex tasks such as supporting the diagnosis and treatment of diseases [1]. Atherosclerosis, the formation of plaque inside of human arteries, is the underlying cause for about 30 % of all deaths worldwide [2]. ...
As one of the most prevalent diseases worldwide, plaque formation in human arteries, known as atherosclerosis, is the focus of many research efforts. Previously, molecular communication (MC) models have been proposed to capture and analyze the natural processes inside the human body and to support the development of diagnosis and treatment methods. In the future, synthetic MC networks are envisioned to span the human body as part of the Internet of Bio-Nano Things (IoBNT), turning blood vessels into physical communication channels. By observing and characterizing changes in these channels, MC networks could play an active role in detecting diseases like atherosclerosis. In this paper, building on previous preliminary work for simulating an MC scenario in a plaque-obstructed blood vessel, we evaluate different analytical models for non-Newtonian flow and derive associated channel impulse responses (CIRs). Additionally, we add the crucial factor of flow pulsatility to our simulation model and investigate the effect of the systole-diastole cycle on the received particles across the plaque channel. We observe a significant influence of the plaque on the channel in terms of the flow profile and CIR across different emission times in the cycle. These metrics could act as crucial indicators for early non-invasive plaque detection in advanced future MC methods.
... Although this variety does not allow us to provide generalized design and implementation solutions, it has produced notable potential for both research and applications. In particular, this has therefore led to the concept of the so-called Internet of Nano-Things (IoNT) [4], capable of supporting various applications, ranging from biomedical to industrial applications [7], [10]. ...
... Another example is the Internet of Bio-Nano Things (IoBNT), in which gateways receive molecular information inside the body, e.g., along the CVS, and then transmit the information via EM signals to an external computational unit, which performs processing and evaluation. These gateways work bidirectionally, i.e., they can also receive EM signals from the computational unit and convert them into a molecular signal for internal transmission, thereby seamlessly integrating both communication paradigms to enable, e.g., health monitoring and personalized treatment [3]. ...
The notion of synthetic molecular communication (MC) refers to the transmission of information via molecules and is largely foreseen for use within the human body, where traditional electromagnetic wave (EM)-based communication is impractical. MC is anticipated to enable innovative medical applications, such as early-stage tumor detection, targeted drug delivery, and holistic approaches like the Internet of Bio-Nano Things (IoBNT). Many of these applications involve parts of the human cardiovascular system (CVS), here referred to as networks, posing challenges for MC due to their complex, highly branched vessel structures. To gain a better understanding of how the topology of such branched vessel networks affects the reception of a molecular signal at a target location, e.g., the network outlet, we present a generic analytical end-to-end model that characterizes molecule propagation and reception in linear branched vessel networks (LBVNs). We specialize this generic model to any MC system employing superparamagnetic iron-oxide nanoparticles (SPIONs) as signaling molecules and a planar coil as receiver (RX). By considering components that have been previously established in testbeds, we effectively isolate the impact of the network topology and validate our theoretical model with testbed data. Additionally, we propose two metrics, namely the molecule delay and the multi-path spread, that relate the LBVN topology to the molecule dispersion induced by the network, thereby linking the network structure to the signal-to-noise ratio (SNR) at the target location. This allows the characterization of the SNR at any point in the network solely based on the network topology. Consequently, our framework can, e.g., be exploited for optimal sensor placement in the CVS or identification of suitable testbed topologies for given SNR requirements.
The Internet of Bio-Nano Things (IoBNT) is collaborative cell biology and nanodevice technology interacting through Molecular Communication (MC). The IoBNT can be accomplished by using the Information and Communication Theory (ICT) study of biological networks. Various technologies such as the Internet of Nano Things (IoNT), the Internet of Bio-degradable Things (IoBDT) and the Internet of Ingestible Things (IoIT) contribute to the development of IoBNT. Our survey discussed the Bio-Nano network and the role of IoT-based technologies along with a comparative study from various literature. We surveyed the various applications of IoNT in which the drug delivery for Insulin-Glucose system is prominent. Our survey aims to provide information about the Insulin-Glucose system involving the IoBNT and MC. We described the details of various factors for a diabetes analysis. We surveyed the diffusion coefficients of Insulin, Glucose and the various parameters that influence insulin production in the body. Our survey identifies the security aspects of IoBNT such as attacks in nanonetworks, bio-cyber interface, Insulin-Glucose system and their possible mitigation techniques. Our survey also provides a hierarchical model of the Bio-Nano network collaborating all the related technologies. Finally, our survey includes the research challenges involved in the proper handling of the IoBNT.
Particulate Drug Delivery Systems (PDDS) are therapeutic methods that use nanoparticles to achieve their healing effects at the exact time, concentration level of drug nanoparticles, and location in the body, while minimizing the effects on other healthy locations. The Molecular Communication (MC) paradigm, where the transmitted message is the drug injection process, the channel is the cardiovascular system, and the received message is the drug reception process, has been investigated as a tool to study nanoscale biological and medical systems in recent years. In this paper, the various noise effects that cause uncertainty in the cardiovascular system are analyzed, modeled, and evaluated from the information theory perspective. Analytical MC noises are presented to include all end-to-end noise effects, from the drug injection, to the absorption of drug nanoparticles by the diseased cells, in the presence of a time-varying and turbulent blood flow. The PDDS capacity is derived analytically including all these noise effects and the constraints on the drug injection. The proposed MC noise is validated by using the kinetic Monte-Carlo simulation technique. Analytical expressions of the noise and the capacity are derived, and MC is presented as a framework for the optimization of particulate drug delivery systems (PDDS).
Molecular communications is a new paradigm that enables nanomachines to communicate within a biological environment. One form of molecular communications is calcium (Ca) signaling, which occurs naturally in living biological cells. Ca signaling enables cells in a tightly packed tissue structure to communicate at short ranges with neighboring cells. The achievable mutual information of Ca signaling between tissue embedded nanomachines is investigated in this paper, focusing in particular on the impact that the deformation of the tissue structure has on the communication channel. Based on this analysis, a number of transmission protocols are proposed; nanomachines can utilize these to communicate using Ca signaling. These protocols are static time-slot configuration, dynamic time-slot configuration, dynamic time-slot configuration with silent communication, and improved dynamic time-slot configuration with silent communication (IDTC-SC). The results of a simulation study show that IDTC-SC provides the maximum data rate when tissues experience frequent deformation.
The goal of a Drug Delivery System (DDS) is to convey a drug where the medication is needed, while, at the same time, preventing the drug from affecting other healthy parts of the body. Drugs composed of micro or nano-sized particles (particulate DDS) that are able to cross barriers which prevent large particles from escaping the bloodstream are used in the most advanced solutions.Molecular Communication (MC) is used as an abstraction of the propagation of drug particles in the body. MC is a new paradigm in communication research where the exchange of information is achieved through the propagation of molecules. Here, the transmitter is the drug injection, the receiver is the drug delivery and the channel is realized by the transport of drug particles, thus enabling the analysis and design of a particulate DDS using communication tools. This is achieved by modeling the MC channel as two separate contributions, namely, the cardiovascular network model and the drug propagation network. The cardiovascular network model allows to analytically compute the blood velocity profile in every location of the cardiovascular system given the flow input by the heart. The drug propagation network model allows the analytical expression of the drug delivery rate at the targeted site given the drug injection rate. Numerical results are also presented to assess the flexibility and accuracy of the developed model. The study of novel optimization techniques for a more effective and less invasive drug delivery will be aided by this model, while paving the way for novel communication techniques for Intra-Body communication Networks (IBN).
Background
Realizing constructive applications of synthetic biology requires continued development of enabling technologies as well as policies and practices to ensure these technologies remain accessible for research. Broadly defined, enabling technologies for synthetic biology include any reagent or method that, alone or in combination with associated technologies, provides the means to generate any new research tool or application. Because applications of synthetic biology likely will embody multiple patented inventions, it will be important to create structures for managing intellectual property rights that best promote continued innovation. Monitoring the enabling technologies of synthetic biology will facilitate the systematic investigation of property rights coupled to these technologies and help shape policies and practices that impact the use, regulation, patenting, and licensing of these technologies.
Results
We conducted a survey among a self-identifying community of practitioners engaged in synthetic biology research to obtain their opinions and experiences with technologies that support the engineering of biological systems. Technologies widely used and considered enabling by survey participants included public and private registries of biological parts, standard methods for physical assembly of DNA constructs, genomic databases, software tools for search, alignment, analysis, and editing of DNA sequences, and commercial services for DNA synthesis and sequencing. Standards and methods supporting measurement, functional composition, and data exchange were less widely used though still considered enabling by a subset of survey participants.
Conclusions
The set of enabling technologies compiled from this survey provide insight into the many and varied technologies that support innovation in synthetic biology. Many of these technologies are widely accessible for use, either by virtue of being in the public domain or through legal tools such as non-exclusive licensing. Access to some patent protected technologies is less clear and use of these technologies may be subject to restrictions imposed by material transfer agreements or other contract terms. We expect the technologies considered enabling for synthetic biology to change as the field advances. By monitoring the enabling technologies of synthetic biology and addressing the policies and practices that impact their development and use, our hope is that the field will be better able to realize its full potential.
Molecular communication (MC) is a promising bio-inspired paradigm for the interconnection of autonomous nanotechnology-enabled devices, or nanomachines, into nanonetworks. MC realizes the exchange of information through the transmission, propagation, and reception of molecules, and it is proposed as a feasible solution for nanonetworks. This idea is motivated by the observation of nature, where MC is successfully adopted by cells for intracellular and intercellular communication. MC-based nanonetworks have the potential to be the enabling technology for a wide range of applications, mostly in the biomedical, but also in the industrial and surveillance fields. The focus of this article is on the most fundamental type of MC, i.e., diffusion-based MC, where the propagation of information-bearing molecules between a transmitter and a receiver is realized through free diffusion in a fluid. The objectives of the research presented in this article are to analyze an MC link from the point of view of communication engineering and information theory, and to provide solutions to the modeling and design of MC-based nanonetworks. First, a deterministic model is realized to study each component, as well as the overall diffusion-based- MC link, in terms of gain and delay. Second, the noise sources affecting a diffusion-based-MC link are identified and statistically modeled. Third, upper/lower bounds to the capacity are derived to evaluate the information-theoretic performance of diffusion-based MC. Fourth, an analysis of the interference produced by multiple diffusion-based MC links in a nanonetwork is provided. This research provides fundamental results that establish a basis for the modeling, design, and realization of future MC-based nanonetworks, as novel technologies and tools are being developed.
Recent advances in synthetic biology, in particular towards the engineering of DNA-based circuits, are providing tools to program man-designed functions within biological cells, thus paving the way for the realization of biological nanoscale devices, known as nanomachines. By stemming from the way biological cells communicate in the nature, Molecular Communication (MC), i.e., the exchange of information through the emission, propagation, and reception of molecules, has been identified as the key paradigm to interconnect these biological nanomachines into nanoscale networks, or nanonetwork. The design of MC nanonetworks built upon biological circuits is particularly interesting since cells possess many of the elements required to realize this type of communication, thus enabling the design of cooperative functions in the biological environment. In this paper, a systems-theoretic modeling is realized by analyzing a minimal subset of biological circuit elements necessary to be included in an MC nanonetwork design where the message-bearing molecules are propagated via free diffusion between two cells. The obtained system-theoretic models stem from the biochemical processes underlying cell-to-cell MC, and are analytically characterized by their transfer functions, attenuation and delay experienced by an information signal exchanged by the communicating cells. Numerical results are presented to evaluate the obtained analytical expressions as functions of realistic biological parameters.
Artificial cellular systems are minimal systems that mimic certain properties of natural cells, including signaling pathways, membranes, and metabolic pathways. These artificial cells (or protocells) can be constructed following a synthetic biology approach by assembling biomembranes, synthetic gene circuits, and cell‐free expression systems. As artificial cells are built from bottom‐up using minimal and a defined number of components, they are more amenable to predictive mathematical modeling and engineered controls when compared with natural cells. Indeed, artificial cells have been implemented as drug delivery machineries and in situ protein expression systems. Furthermore, artificial cells have been used as biomimetic systems to unveil new insights into functions of natural cells, which are otherwise difficult to investigate owing to their inherent complexity. It is our vision that the development of artificial cells would bring forth parallel advancements in synthetic biology, cell‐free systems, and in vitro systems biology.
This article is categorized under: Nanotechnology Approaches to Biology > Cells at the Nanoscale
Nanotechnology Approaches to Biology > Nanoscale Systems in Biology
This article presents a branch of research where the use of molecules to encode and transmit information among nanoscale devices (nanomachines) is investigated as a bio-inspired viable solution to realize nano-communication networks. Unlike traditional technologies, molecular communication is a radically new paradigm, which demands novel solutions, including the identification of naturally existing molecular communication mechanisms, the establishment of the foundations of a molecular information theory, or the development of architectures and networking protocols for nanomachines. The tight connection of this cutting edge engineering research field with biology will ultimately enable both the bio-inspired study of molecular nanonetwork architectures and their realization with tools already available in nature. The testbed described in this article, which is based on a microfluidic device hosting intercommunicating populations of genetically engineered bacteria, is a clear example of this research direction.
This paper reviews recent developments in the design and application of two types of optical nanosensor, those based on: (1) localized surface plasmon resonance (LSPR) spectroscopy and (2) surface-enhanced Raman scattering (SERS). The performance of these sensors is discussed in the context of biological and chemical sensing. The first section addresses the LSPR sensors. Arrays of nanotriangles were evaluated and characterized using realistic protein/ligand interactions. Isolated, single nanoparticles were used for chemosensing and performed comparably to the nanoparticle array sensors. In particular, we highlight the effect of nanoparticle morphology on sensing response. The second section details the use of SERS sensors using metal film over nanosphere (MFON) surfaces. The high SERS enhancements and long-term stability of MFONs were exploited in order to develop SERS-based sensors for two important target molecules: a Bacillus anthracis biomarker and glucose in a serum protein mixture.