{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T08:19:32Z","timestamp":1788337172987,"version":"build-2803163510"},"reference-count":21,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T00:00:00Z","timestamp":1788307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Heterogeneous sensor systems generate measurements in incompatible physical units, which complicates their direct integration with photonic stochastic processors. This study proposes an architecture-level event-oriented frontend that converts heterogeneous sensor channels into unified event-oriented probabilities and then into Bernoulli bitstreams compatible with polarization-encoded optical interfaces. The framework combines sensor-to-probability mapping, weighted event-level fusion, stochastic bitstream generation, and system-level control of correlation and synchronization. Its performance was investigated through reproducible Colab-based modeling using baseline validation, weighting-strategy comparison, static and time-varying decorrelation\/synchronization studies, and robustness\/scaling analysis. The validation framework also includes a first-order analysis of photonic-interface nonidealities and a semi-real validation case using a digitized 520 nm optical smoke-transmittance response from the literature. The results show that the stochastic event estimate converges toward the float reference with increasing bitstream length, reliability-aware weighting outperforms equal and tested data-driven weighting in the benchmark, independent stream generation provides the best inference quality, and synchronization mismatch becomes measurable in time-varying fusion. The frontend also demonstrates graceful degradation under channel corruption and favorable scaling under mixed informative, weak, redundant, conflicting, and noisy channel configurations. These findings indicate that heterogeneous sensors can be interfaced with photonic stochastic systems through a common event-level representation and that weighting, decorrelation, synchronization, and robustness must be treated as core frontend design variables.<\/jats:p>","DOI":"10.3390\/s26175565","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T07:53:11Z","timestamp":1788335591000},"page":"5565","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Architecture-Level Event-Oriented Frontend for Heterogeneous Sensor Inference in Photonic Stochastic Systems"],"prefix":"10.3390","volume":"26","author":[{"given":"Oleg","family":"Angelsky","sequence":"first","affiliation":[{"name":"Department of Correlation Optics, Yuriy Fedkovych Chernivtsi National University, Kotsiubynskoho Street, 58002 Chernivtsi, Ukraine"},{"name":"Optoelectronic Information Center, Taizhou Institute of Zhejiang University, Taizhou 318000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9549-2198","authenticated-orcid":false,"given":"Myroslav","family":"Strynadko","sequence":"additional","affiliation":[{"name":"Department of Correlation Optics, Yuriy Fedkovych Chernivtsi National University, Kotsiubynskoho Street, 58002 Chernivtsi, Ukraine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9108-8591","authenticated-orcid":false,"given":"Claudia","family":"Zenkova","sequence":"additional","affiliation":[{"name":"Department of Correlation Optics, Yuriy Fedkovych Chernivtsi National University, Kotsiubynskoho Street, 58002 Chernivtsi, Ukraine"},{"name":"Optoelectronic Information Center, Taizhou Institute of Zhejiang University, Taizhou 318000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2701-6380","authenticated-orcid":false,"given":"Roman","family":"Zaiats","sequence":"additional","affiliation":[{"name":"Department of Correlation Optics, Yuriy Fedkovych Chernivtsi National University, Kotsiubynskoho Street, 58002 Chernivtsi, Ukraine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8128-3273","authenticated-orcid":false,"given":"Xinzheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"The MOE Key Laboratory of Weak-Light Nonlinear Photonics, TEDA Institute of Applied Physics and School of Physics, Nankai University, Tianjin 300457, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Zheng","sequence":"additional","affiliation":[{"name":"Optoelectronic Information Center, Taizhou Institute of Zhejiang University, Taizhou 318000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingxian","family":"Cai","sequence":"additional","affiliation":[{"name":"Optoelectronic Information Center, Taizhou Institute of Zhejiang University, Taizhou 318000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.cja.2023.12.009","article-title":"Multi-source information fusion: Progress and future","volume":"37","author":"Li","year":"2024","journal-title":"Chin. J. Aeronaut."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Shaikh, Z.A., Van Hamme, D., Veelaert, P., and Philips, W. (2022). Probabilistic fusion for pedestrian detection from thermal and colour images. Sensors, 22.","DOI":"10.3390\/s22228637"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Rabb, E., and Steckenrider, J.J. (2023). Walking trajectory estimation using multi-sensor fusion and a probabilistic step model. Sensors, 23.","DOI":"10.3390\/s23146494"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Qian, H., Wang, M., Zhu, M., and Wang, H. (2025). A review of multi-sensor fusion in autonomous driving. Sensors, 25.","DOI":"10.3390\/s25196033"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1145\/2465787.2465794","article-title":"Survey of stochastic computing","volume":"12","author":"Alaghi","year":"2013","journal-title":"ACM Trans. Embed. Comput. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"011305","DOI":"10.1063\/1.5055860","article-title":"p-bits for probabilistic spin logic","volume":"6","author":"Camsari","year":"2019","journal-title":"Appl. Phys. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1038\/s41586-020-03063-0","article-title":"11 TOPS photonic convolutional accelerator for optical neural networks","volume":"589","author":"Xu","year":"2021","journal-title":"Nature"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1038\/s41566-023-01313-x","article-title":"Higher-dimensional processing using a photonic tensor core with continuous-time data","volume":"17","author":"Dong","year":"2023","journal-title":"Nat. Photonics"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.eng.2021.06.021","article-title":"Analog optical computing for artificial intelligence","volume":"10","author":"Wu","year":"2022","journal-title":"Engineering"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.eng.2024.08.016","article-title":"Intelligent photonics: A disruptive technology to shape the present and redefine the future","volume":"46","author":"Xu","year":"2025","journal-title":"Engineering"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/s44335-025-00040-6","article-title":"Edge intelligence through in-sensor and near-sensor computing for the artificial intelligence of things","volume":"2","author":"Baek","year":"2025","journal-title":"npj Unconv. Comput."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"10136","DOI":"10.1038\/s41467-025-65151-x","article-title":"Photonic edge intelligence chip for multi-modal sensing, inference and learning","volume":"16","author":"Zhang","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Xue, H., Zhang, M., Yu, P., Zhang, H., Wu, G., Li, Y., and Zheng, X. (2021). A novel multi-sensor fusion algorithm based on uncertainty analysis. Sensors, 21.","DOI":"10.3390\/s21082713"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"108241","DOI":"10.1016\/j.sigpro.2021.108241","article-title":"Event driven sensor fusion","volume":"188","author":"Roheda","year":"2021","journal-title":"Signal Process."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.inffus.2021.09.017","article-title":"On the use of information fusion techniques to improve information quality: Taxonomy, opportunities and challenges","volume":"78","author":"Paggi","year":"2022","journal-title":"Inf. Fusion"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"42195","DOI":"10.1109\/JSEN.2024.3456577","article-title":"MECKD: Deep learning-based fall detection in multilayer mobile edge computing with knowledge distillation","volume":"24","author":"Mao","year":"2024","journal-title":"IEEE Sens. J."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Angelsky, O.V., Bekshaev, A.Y., Zenkova, C.Y., Ivansky, D.I., and Zheng, J. (2022). Correlation Optics, Coherence and Optical Singularities: Basic Concepts and Practical Applications. Front. Phys., 10.","DOI":"10.3389\/fphy.2022.924508"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Xu, H., Xu, Z., Ren, Q., Meng, Y., Han, S., Wang, Z., Chai, Y., Bae, S.H., and Hu, W. (2026). Two-dimensional materials for integrated sensing. Nat. Mater., Online ahead of print.","DOI":"10.1038\/s41563-026-02551-4"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.1038\/s41566-025-01759-1","article-title":"Guidelines for accurate evaluation of photodetectors based on emerging semiconductor technologies","volume":"19","author":"Pecunia","year":"2025","journal-title":"Nat. Photonics"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2683","DOI":"10.1007\/s10694-021-01139-5","article-title":"Multi-Wavelength Densitometer for Experimental Research on the Optical Characteristics of Smoke Layers","volume":"57","author":"Antosiewicz","year":"2021","journal-title":"Fire Technol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Angelsky, O., Strynadko, M., Zenkova, C., Zaiats, R., Zhang, X., Zheng, J., and Cai, J. (Preprints, 2026). Universal Sensor Frontend for Event Inference in Photonic Stochastic Systems, Preprints, in press.","DOI":"10.20944\/preprints202603.2303.v1"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/17\/5565\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T07:53:58Z","timestamp":1788335638000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/17\/5565"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,2]]},"references-count":21,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["s26175565"],"URL":"https:\/\/doi.org\/10.3390\/s26175565","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,2]]}}}