Next-Generation Food Safety Monitoring Using Biosensors and Internet-of-Things Technologies

Introduction

Food safety has emerged as a global public health and economic concern in the twenty-first century. The complexity of modern food systems, which involve international trade, mass production, and long supply chains, has amplified the risks associated with foodborne hazards. According to the World Health Organization (WHO, 2020), approximately 600 million people suffer from foodborne illnesses each year, leading to an estimated 420,000 deaths. Beyond the human health burden, unsafe food incurs significant economic costs through lost productivity, medical expenses, trade restrictions, and reputational damage to food industries [1]. The urgency of addressing food safety is further intensified by rising consumer expectations for transparency, traceability, and sustainability in food systems.

Conventional approaches to food safety monitoring, such as culture-based microbial analysis, chromatographic methods, and immunological assays, have been the cornerstone of quality assurance for decades. While these techniques are accurate and widely accepted by regulatory agencies, they suffer from inherent limitations. Most are time-consuming, requiring hours to days for results, and involve labor-intensive laboratory protocols that are not practical for continuous or real-time monitoring. Furthermore, such methods often demand specialized infrastructure and trained personnel, making them less feasible for small-scale producers, developing economies, or decentralized monitoring across complex supply chains [2]. These limitations highlight a growing gap between traditional food safety strategies and the evolving needs of globalized, high-volume, and fast-moving food industries.

The technological innovations are reshaping the future of food safety monitoring. Among them, biosensors have attracted significant attention due to their ability to provide rapid, sensitive, and specific detection of contaminants. Biosensors are analytical devices that combine biological recognition elements with physical or chemical transducers to convert biochemical interactions into quantifiable signals [3]. They can be tailored to detect a wide range of hazards, including microbial pathogens such as Escherichia coli, Salmonella spp., and Listeria monocytogenes, as well as chemical residues, toxins, allergens, and heavy metals. Recent advancements in nanomaterials, microfluidics, and signal amplification technologies have enhanced the sensitivity and portability of biosensors, making them increasingly suitable for on-site and real-time applications [4]. Equally transformative is the emergence of the Internet of Things (IoT) in food safety monitoring. The IoT refers to a network of interconnected devices equipped with sensors, communication protocols, and cloud-based data storage systems that enable real-time collection, transmission, and analysis of information. In food systems, IoT technologies have been applied to monitor environmental parameters such as temperature, humidity, and gas concentrations, which are critical indicators of food quality and safety. When integrated with biosensors, IoT provides an intelligent infrastructure capable of continuous monitoring, remote accessibility, and predictive analytics [5]. This integration allows stakeholders—including farmers, processors, distributors, regulators, and consumers—to access real-time information, thereby enabling faster responses to contamination events and improving overall supply chain transparency.

Practical applications of biosensor-IoT systems are already visible in several domains. Smart packaging embedded with biosensors and IoT connectivity can monitor spoilage indicators, providing consumers with real-time updates on product freshness. Cold-chain logistics benefit from IoT-enabled biosensors that track perishable products during transportation and storage, ensuring compliance with food safety standards. At the production level, portable biosensor devices connected to mobile applications enable on-site pathogen detection, reducing reliance on centralized laboratories and minimizing delays in decision-making [6]. In addition, the integration of IoT data with blockchain technologies is revolutionizing traceability, creating immutable digital records that enhance consumer trust and regulatory oversight.Despite these promising developments, challenges persist in achieving widespread adoption of biosensor-IoT systems. Standardization and regulatory validation remain significant barriers, as biosensors must demonstrate consistent performance across diverse contexts before gaining official acceptance. Cost and scalability issues limit accessibility, particularly in low-resource settings where food safety risks are often most severe [7]. Furthermore, IoT-based systems introduce concerns related to data privacy, cybersecurity, and interoperability between devices and platforms. Addressing these challenges requires collaborative efforts among researchers, policymakers, and industry stakeholders to establish robust frameworks that balance innovation with reliability and security.

The convergence of biosensor and IoT technologies represents a paradigm shift in how food safety is approached, transitioning from reactive, laboratory-based analyses to proactive, real-time monitoring across the entire food supply chain. This shift has the potential not only to reduce the incidence of foodborne illnesses but also to reshape consumer trust, regulatory frameworks, and industry competitiveness. By leveraging advances in artificial intelligence, nanotechnology, and blockchain integration, next-generation monitoring systems can become even more predictive, intelligent, and automated [8]. The objective of this article is to provide a comprehensive review of current advances in biosensors for food safety, their integration with IoT technologies, and the implications for future food monitoring systems. It highlights applications in smart packaging, cold-chain management, and pathogen detection, while also addressing limitations and future opportunities. Ultimately, this article argues that biosensor-IoT platforms have the potential to become the backbone of global food safety management, fostering safer, more transparent, and more sustainable food systems.

Principles of Biosensors

Biosensors are analytical devices that integrate a biological recognition element with a physical or chemical transducer to generate measurable signals in response to specific analytes. The biological components may include enzymes, antibodies, nucleic acids, aptamers, or even whole microbial cells, each selected for its ability to specifically interact with a target molecule. The transducer then converts this biochemical interaction into quantifiable signals—such as electrical, optical, or thermal responses—that can be measured and analyzed. By combining the specificity of biological recognition with the precision of modern signal transduction, biosensors provide rapid, sensitive, and often portable solutions for food safety monitoring [9]. In food safety applications, biosensors are widely employed to detect microbial pathogens such as Escherichia coli, Salmonella spp., and Listeria monocytogenes, which are responsible for severe foodborne outbreaks worldwide. They are also utilized for monitoring chemical contaminants, including pesticide residues, heavy metals, toxins, and allergens, which pose chronic health risks and economic burdens when undetected [10].

Types of Biosensors Used in Food Safety

A diverse range of biosensor platforms has been developed, each optimized for specific detection requirements. The major categories include:

• Electrochemical biosensors – These devices measure electrical signals, such as current, voltage, or impedance, generated during biochemical interactions. Due to their high sensitivity, low cost, and ease of miniaturization, electrochemical biosensors are widely applied for detecting pathogens and toxins in food matrices [11].
• Optical biosensors – Optical approaches rely on detecting changes in light properties, such as fluorescence, absorbance, or refractive index, following a recognition event. Technologies such as surface plasmon resonance and colorimetric assays allow label-free detection, high throughput, and potential for real-time monitoring [12].
• Nanomaterial-based biosensors – Incorporating nanomaterials such as gold nanoparticles, carbon nanotubes, or quantum dots significantly enhances sensitivity and lowers detection limits. These biosensors exploit the unique optical, electronic, and catalytic properties of nanomaterials to amplify signals, making them highly effective for trace-level detection of pathogens and contaminants [13].
• Paper-based biosensors – Emerging as low-cost, portable, and user-friendly platforms, paper-based biosensors offer rapid point-of-care detection. They utilize simple colorimetric or electrochemical outputs, making them suitable for resource-limited settings and field applications [14].

Compared to conventional culture-based methods, which require several days for microbial identification, biosensors dramatically shorten detection times to a matter of minutes or hours. This rapid response not only reduces the risks associated with foodborne outbreaks but also supports real-time decision-making in supply chain management and regulatory compliance (Mehrotra, 2016).

The Role of IoT in Food Safety

The Internet of Things (IoT) has emerged as a transformative framework in food safety monitoring, offering intelligent and interconnected systems capable of real-time data acquisition, processing, and communication. By integrating biosensors with wireless networks, cloud computing, and mobile applications, IoT platforms enable continuous monitoring across the entire food supply chain—from primary production and processing to storage, distribution, and consumer use. This interconnected infrastructure ensures that safety-critical data is accessible to all stakeholders, including farmers, food processors, regulators, distributors, and end consumers, thereby enhancing transparency, traceability, and accountability [15]. IoT-based food safety monitoring systems typically comprise three core components: (1) sensing devices such as biosensors and environmental sensors that collect data on microbial pathogens, chemical contaminants, or storage conditions; (2) communication technologies including RFID, Bluetooth, Wi-Fi, and 5G that facilitate data transmission; and (3) data management platforms such as cloud servers and mobile interfaces that process and present information for decision-making. Together, these elements create a dynamic ecosystem capable of not only detecting hazards but also predicting risks through advanced analytics.

Applications of IoT-Enabled Biosensor Systems

The integration of biosensors with IoT technologies has led to several practical applications in food safety monitoring:

• Smart packaging systems – Packaging embedded with biosensors and wireless transmitters can detect spoilage indicators, microbial growth, or gas emissions and communicate freshness data directly to consumers or retailers. This extends shelf-life management and reduces food waste.
• Cold-chain monitoring – IoT-enabled biosensors track temperature, humidity, and contamination risks during transport and storage of perishable goods. Continuous monitoring ensures compliance with food safety standards and provides alerts in case of deviations, thereby preventing outbreaks and economic losses (Ben-Daya et al., 2019).
• On-site detection and surveillance – Portable biosensors connected to mobile devices allow producers and inspectors to test raw materials or final products in real-time. This minimizes reliance on centralized laboratories and accelerates decision-making in quality assurance.
• Blockchain integration for traceability – IoT systems linked with blockchain create immutable records of food safety data, from farm to fork. This integration enhances trust, ensures authenticity, and improves accountability within the food supply chain (Tian, 2017).

Benefits of IoT Integration

The convergence of IoT and biosensor technologies provides several benefits over conventional monitoring approaches. First, it enables real-time and continuous monitoring, reducing response times during contamination events. Second, it enhances predictive capabilities, as IoT platforms equipped with artificial intelligence (AI) and machine learning can identify risk patterns before hazards escalate [16]. Third, IoT integration supports remote accessibility, allowing stakeholders across geographic boundaries to make informed decisions. Finally, IoT-based systems foster consumer confidence by promoting transparency and enabling direct access to food safety information.

Applications in Food Systems

The integration of biosensors with Internet-of-Things (IoT) technologies has opened new avenues for improving food safety, quality control, and supply chain management. These applications extend beyond simple detection, creating intelligent and interconnected systems that improve transparency, reduce waste, and minimize health risks [17]. Several key applications of IoT-enabled biosensor systems in food systems are highlighted below.

Smart Packaging

Smart packaging represents one of the most promising applications of biosensor–IoT integration. Packaging materials embedded with biosensors can detect spoilage gases (e.g., volatile amines and sulfur compounds), microbial activity, or temperature fluctuations. These biosensors transmit real-time data to smartphones or cloud platforms, allowing consumers, retailers, and producers to track freshness and product safety [4]. By extending shelf-life management, smart packaging reduces food waste and promotes consumer confidence in perishable products such as meat, dairy, and seafood.

Cold Chain Monitoring

Maintaining an unbroken cold chain is essential for preserving the quality and safety of perishable foods during storage and transportation. IoT-enabled biosensors and environmental sensors embedded in transport containers or storage units monitor temperature, humidity, and microbial risks continuously. Data is transmitted to centralized systems or mobile applications, ensuring compliance with safety standards and providing alerts when conditions deviate from acceptable ranges. Such monitoring reduces the risk of foodborne outbreaks, financial losses, and regulatory violations [9].

On-Site Pathogen Detection

Portable biosensors integrated with IoT platforms allow rapid, on-site detection of pathogens in various food system environments, including farms, slaughterhouses, markets, and food processing facilities. These devices reduce dependence on centralized laboratories, where testing is often time-consuming and costly. By providing immediate results, IoT-connected portable biosensors enable real-time decision-making for quality assurance and hazard control. This approach is particularly valuable in regions with limited laboratory infrastructure or in contexts requiring high-frequency testing.

Blockchain Integration for Traceability

The combination of IoT-enabled biosensor data with blockchain technology offers a powerful solution for achieving transparency and accountability across food supply chains. Blockchain provides immutable records of safety-related information—from farm-level production practices to distribution and retail. IoT devices feed real-time biosensor data into blockchain ledgers, ensuring data integrity and reducing the risk of fraud or mislabeling. This integration improves consumer trust, enhances regulatory compliance, and strengthens global food trade networks [7].

Challenges and Limitations

Despite rapid advances in biosensor and IoT technologies for food safety monitoring, several challenges and limitations remain that hinder large-scale adoption and regulatory acceptance. These challenges span technical, economic, and institutional dimensions, highlighting the need for continued innovation and policy support.

Standardization

One of the major barriers to commercialization and regulatory approval of biosensor-based systems is the lack of standardized validation protocols. Biosensors vary widely in terms of design, sensitivity, specificity, and detection mechanisms, which complicates benchmarking and regulatory acceptance across jurisdictions [6]. Without harmonized guidelines, stakeholders may find it difficult to trust data generated by different biosensor platforms, slowing down their integration into mainstream food safety monitoring systems.

Scalability and Cost

Although biosensor–IoT platforms demonstrate remarkable performance at the laboratory and pilot scale, their mass production and commercialization face challenges. High costs associated with sensor fabrication, nanomaterial synthesis, calibration, and IoT integration often limit their affordability, especially in resource-constrained settings [6]. Moreover, many biosensors require specialized storage and handling conditions, further complicating their scalability for widespread use in food supply chains.

Data Security and Privacy

IoT-enabled biosensor systems rely on continuous data transmission and cloud-based storage, making them vulnerable to cybersecurity risks. Unauthorized access, data manipulation, or hacking incidents can compromise food safety data and undermine consumer trust [9]. Ensuring robust encryption, secure communication protocols, and compliance with data protection regulations is essential for safeguarding sensitive information generated by these systems.

Integration and Interoperability

The food industry relies on diverse devices, platforms, and stakeholders, making seamless integration a considerable challenge. IoT-enabled biosensors must operate within heterogeneous networks involving different communication standards (e.g., Wi-Fi, 5G, RFID), databases, and software systems. Ensuring interoperability across these infrastructures requires robust frameworks and international collaboration to establish universal communication and data-sharing protocols [3].

Future Perspectives

Future food safety monitoring will likely rely on fully automated, AI-driven biosensor-IoT systems. Emerging technologies such as nanotechnology, machine learning, and blockchain will further enhance accuracy, predictive capability, and supply chain transparency. Personalized consumer apps connected to smart packaging could empower individuals to verify food safety in real time. Additionally, advances in wearable biosensors and environmental biosensing will extend applications to household and restaurant settings.

Conclusion

Next-generation food safety monitoring signifies a paradigm shift from conventional, laboratory-based testing methods toward real-time, intelligent, and interconnected systems. Unlike traditional microbiological or chemical analyses, which are often labor-intensive and time-consuming, the integration of biosensors with Internet-of-Things (IoT) technologies enables continuous surveillance across the entire food supply chain. This transformation allows hazards to be detected at the earliest stages, ensuring faster response times, greater compliance with regulatory frameworks, and enhanced consumer confidence in food products.Biosensors serve as the cornerstone of these systems, offering rapid, sensitive, and specific detection of microbial pathogens, toxins, and chemical contaminants. When embedded into IoT-enabled networks, these devices not only collect but also transmit critical safety data to cloud platforms, mobile applications, and blockchain systems. This convergence enhances transparency, facilitates traceability, and supports decision-making for stakeholders ranging from farmers and processors to regulators and consumers. Furthermore, applications such as smart packaging, cold chain monitoring, and on-site pathogen detection illustrate the versatility and scalability of biosensor–IoT platforms across diverse food system environments, significant challenges remain. High production costs, lack of standardization in biosensor validation, issues of interoperability, and cybersecurity vulnerabilities represent barriers to widespread adoption. Addressing these limitations will require coordinated efforts involving technological innovation, regulatory harmonization, and cross-sectoral collaboration. Emerging solutions such as nanomaterial-enhanced biosensors, AI-driven predictive analytics, and blockchain integration hold promise for overcoming current constraints and establishing resilient food safety infrastructures, the global shift toward digitalization, precision agriculture, and sustainable food systems is likely to accelerate the deployment of biosensor–IoT platforms. As these technologies mature, they are poised to become the backbone of modern food safety management, safeguarding public health while fostering transparency, efficiency, and sustainability in global food supply chains.

References

1. Mayer, M., &Baeumner, A. J. (2019). A megatrend challenging analytical chemistry: biosensor and chemosensor concepts ready for the internet of things. Chemical reviews, 119(13), 7996-8027.
2. Pateraki, Maria, Konstantinos Fysarakis, Vangelis Sakkalis, Georgios Spanoudakis, IraklisVarlamis, MichailManiadakis, ManolisLourakis et al. “Biosensors and Internet of Things in smart healthcare applications: Challenges and opportunities.” Wearable and implantable medical devices (2020): 25-53.
3. Sahu, K. S., Majowicz, S. E., Dubin, J. A., & Morita, P. P. (2021). NextGen public health surveillance and the internet of things (IoT). Frontiers in Public Health, 9, 756675.
4. Maksimović, M., Omanović-Mikličanin, E., &Badnjević, A. (2019). Nanofood and internet of nano things. Springer International Publishing.
5. Zafar, Sidra, Mohsin Nazir, TaimurBakhshi, Hasan Ali Khattak, Sarmadullah Khan, Muhammad Bilal, Kim-Kwang Raymond Choo, Kyung-Sup Kwak, and Aneeqa Sabah. “A systematic review of bio-cyber interface technologies and security issues for internet of bio-nano things.” IEEE Access 9 (2021): 93529-93566.
6. Irkham, I., Ibrahim, A. U., Nwekwo, C. W., Al-Turjman, F., &Hartati, Y. W. (2022). Current technologies for detection of COVID-19: Biosensors, artificial intelligence and internet of medical things (IOMT). Sensors, 23(1), 426.
7. Lalpawimawha, L. V., &Lalruatfela, B. (2019). Proceedings of National Workshop on Sensor Networks, Internet of Things and Internet of Everything. Notion Press.
8. Phillips, J. D. (2021). Energy harvesting in nanosystems: Powering the next generation of the internet of things. Frontiers in Nanotechnology, 3, 633931.
9. Shafique, K., Khawaja, B. A., Sabir, F., Qazi, S., &Mustaqim, M. (2020). Internet of things (IoT) for next-generation smart systems: A review of current challenges, future trends and prospects for emerging 5G-IoT scenarios. IEEE access, 8, 23022-23040.
10. Shi, Q., Dong, B., He, T., Sun, Z., Zhu, J., Zhang, Z., & Lee, C. (2020). Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things. InfoMat, 2(6), 1131-1162.
11. Paul, P. K. (2022). Aspects of Biosensors with Refers to Emerging Implications of Artificial Intelligence, Big Data and Analytics: The Changing Healthcare–A General Review. Next Generation Smart Nano-Bio-Devices, 1-18.
12. Bhide, A., Ganguly, A., Parupudi, T., Ramasamy, M., Muthukumar, S., & Prasad, S. (2021). Next-generation continuous metabolite sensing toward emerging sensor needs. ACS omega, 6(9), 6031-6040.
13. Okwu, M. O., Tartibu, L. K., Maware, C., Enarevba, D. R., Afenogho, J. O., & Essien, A. (2022, August). Emerging technologies of industry 4.0: Challenges and opportunities. In 2022 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) (pp. 1-13). IEEE.
14. Zhao, G., Guo, Y., Sun, X., & Wang, X. (2015). A system for pesticide residues detection and agricultural products traceability based on acetylcholinesterase biosensor and internet of things. International Journal of Electrochemical Science, 10(4), 3387-3399.
15. Liu, Y., Li, D., Du, B., Shu, L., & Han, G. (2022). Rethinking sustainable sensing in agricultural Internet of Things: From power supply perspective. IEEE Wireless Communications, 29(4), 102-109.
16. Mujawar, M. A., Gohel, H., Bhardwaj, S. K., Srinivasan, S., Hickman, N., & Kaushik, A. (2020). Nano-enabled biosensing systems for intelligent healthcare: towards COVID-19 management. Materials Today Chemistry, 17, 100306.
17. Narayanamurthy, V., Bhuvaneshwari, K. S., Jeroish, Z. E., &Samsuri, F. (2020, March). Lab-On-Chip, Internet of Things, Analytics and Health Care 4.0: a synergistic future forward. In Journal of Physics: Conference Series (Vol. 1502, No. 1, p. 012023). IOP Publishing.